Sample records for quantitative targeted metabolomics

  1. SWATHtoMRM: Development of High-Coverage Targeted Metabolomics Method Using SWATH Technology for Biomarker Discovery.

    PubMed

    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 ).

  2. Sample normalization methods in quantitative metabolomics.

    PubMed

    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.

  3. Multiplexed, quantitative, and targeted metabolite profiling by LC-MS/MRM.

    PubMed

    Wei, Ru; Li, Guodong; Seymour, Albert B

    2014-01-01

    Targeted metabolomics, which focuses on a subset of known metabolites representative of biologically relevant metabolic pathways, is a valuable tool to discover biomarkers and link disease phenotypes to underlying mechanisms or therapeutic modes of action. A key advantage of targeted metabolomics, compared to discovery metabolomics, is its immediate readiness for extracting biological information derived from known metabolites and quantitative measurements. However, simultaneously analyzing hundreds of endogenous metabolites presents a challenge due to their diverse chemical structures and properties. Here we report a method which combines different chromatographic separation conditions, optimal ionization polarities, and the most sensitive triple-quadrupole MS-based data acquisition mode, multiple reaction monitoring (MRM), to quantitatively profile 205 endogenous metabolites in 10 min.

  4. The great importance of normalization of LC-MS data for highly-accurate non-targeted metabolomics.

    PubMed

    Mizuno, Hajime; Ueda, Kazuki; Kobayashi, Yuta; Tsuyama, Naohiro; Todoroki, Kenichiro; Min, Jun Zhe; Toyo'oka, Toshimasa

    2017-01-01

    The non-targeted metabolomics analysis of biological samples is very important to understand biological functions and diseases. LC combined with electrospray ionization-based MS has been a powerful tool and widely used for metabolomic analyses. However, the ionization efficiency of electrospray ionization fluctuates for various unexpected reasons such as matrix effects and intraday variations of the instrument performances. To remove these fluctuations, normalization methods have been developed. Such techniques include increasing the sensitivity, separating co-eluting components and normalizing the ionization efficiencies. Normalization techniques allow simultaneously correcting of the ionization efficiencies of the detected metabolite peaks and achieving quantitative non-targeted metabolomics. In this review paper, we focused on these normalization methods for non-targeted metabolomics by LC-MS. Copyright © 2016 John Wiley & Sons, Ltd.

  5. Targeted metabolomics and medication classification data from participants in the ADNI1 cohort.

    PubMed

    St John-Williams, Lisa; Blach, Colette; Toledo, Jon B; Rotroff, Daniel M; Kim, Sungeun; Klavins, Kristaps; Baillie, Rebecca; Han, Xianlin; Mahmoudiandehkordi, Siamak; Jack, John; Massaro, Tyler J; Lucas, Joseph E; Louie, Gregory; Motsinger-Reif, Alison A; Risacher, Shannon L; Saykin, Andrew J; Kastenmüller, Gabi; Arnold, Matthias; Koal, Therese; Moseley, M Arthur; Mangravite, Lara M; Peters, Mette A; Tenenbaum, Jessica D; Thompson, J Will; Kaddurah-Daouk, Rima

    2017-10-17

    Alzheimer's disease (AD) is the most common neurodegenerative disease presenting major health and economic challenges that continue to grow. Mechanisms of disease are poorly understood but significant data point to metabolic defects that might contribute to disease pathogenesis. The Alzheimer Disease Metabolomics Consortium (ADMC) in partnership with Alzheimer Disease Neuroimaging Initiative (ADNI) is creating a comprehensive biochemical database for AD. Using targeted and non- targeted metabolomics and lipidomics platforms we are mapping metabolic pathway and network failures across the trajectory of disease. In this report we present quantitative metabolomics data generated on serum from 199 control, 356 mild cognitive impairment and 175 AD subjects enrolled in ADNI1 using AbsoluteIDQ-p180 platform, along with the pipeline for data preprocessing and medication classification for confound correction. The dataset presented here is the first of eight metabolomics datasets being generated for broad biochemical investigation of the AD metabolome. We expect that these collective metabolomics datasets will provide valuable resources for researchers to identify novel molecular mechanisms contributing to AD pathogenesis and disease phenotypes.

  6. Targeted metabolomics and medication classification data from participants in the ADNI1 cohort

    PubMed Central

    St John-Williams, Lisa; Blach, Colette; Toledo, Jon B.; Rotroff, Daniel M.; Kim, Sungeun; Klavins, Kristaps; Baillie, Rebecca; Han, Xianlin; Mahmoudiandehkordi, Siamak; Jack, John; Massaro, Tyler J.; Lucas, Joseph E.; Louie, Gregory; Motsinger-Reif, Alison A.; Risacher, Shannon L.; Saykin, Andrew J.; Kastenmüller, Gabi; Arnold, Matthias; Koal, Therese; Moseley, M. Arthur; Mangravite, Lara M.; Peters, Mette A.; Tenenbaum, Jessica D.; Thompson, J. Will; Kaddurah-Daouk, Rima

    2017-01-01

    Alzheimer’s disease (AD) is the most common neurodegenerative disease presenting major health and economic challenges that continue to grow. Mechanisms of disease are poorly understood but significant data point to metabolic defects that might contribute to disease pathogenesis. The Alzheimer Disease Metabolomics Consortium (ADMC) in partnership with Alzheimer Disease Neuroimaging Initiative (ADNI) is creating a comprehensive biochemical database for AD. Using targeted and non- targeted metabolomics and lipidomics platforms we are mapping metabolic pathway and network failures across the trajectory of disease. In this report we present quantitative metabolomics data generated on serum from 199 control, 356 mild cognitive impairment and 175 AD subjects enrolled in ADNI1 using AbsoluteIDQ-p180 platform, along with the pipeline for data preprocessing and medication classification for confound correction. The dataset presented here is the first of eight metabolomics datasets being generated for broad biochemical investigation of the AD metabolome. We expect that these collective metabolomics datasets will provide valuable resources for researchers to identify novel molecular mechanisms contributing to AD pathogenesis and disease phenotypes. PMID:29039849

  7. Development of a Postcolumn Infused-Internal Standard Liquid Chromatography Mass Spectrometry Method for Quantitative Metabolomics Studies.

    PubMed

    Liao, Hsiao-Wei; Chen, Guan-Yuan; Wu, Ming-Shiang; Liao, Wei-Chih; Lin, Ching-Hung; Kuo, Ching-Hua

    2017-02-03

    Quantitative metabolomics has become much more important in clinical research in recent years. Individual differences in matrix effects (MEs) and the injection order effect are two major factors that reduce the quantification accuracy in liquid chromatography-electrospray ionization-mass spectrometry-based (LC-ESI-MS) metabolomics studies. This study proposed a postcolumn infused-internal standard (PCI-IS) combined with a matrix normalization factor (MNF) strategy to improve the analytical accuracy of quantitative metabolomics. The PCI-IS combined with the MNF method was applied for a targeted metabolomics study of amino acids (AAs). D8-Phenylalanine was used as the PCI-IS, and it was postcolumn-infused into the ESI interface for calibration purposes. The MNF was used to bridge the AA response in a standard solution with the plasma samples. The MEs caused signal changes that were corrected by dividing the AA signal intensities by the PCI-IS intensities after adjustment with the MNF. After the method validation, we evaluated the method applicability for breast cancer research using 100 plasma samples. The quantification results revealed that the 11 tested AAs exhibit an accuracy between 88.2 and 110.7%. The principal component analysis score plot revealed that the injection order effect can be successfully removed, and most of the within-group variation of the tested AAs decreased after the PCI-IS correction. Finally, targeted metabolomics studies on the AAs showed that tryptophan was expressed more in malignant patients than in the benign group. We anticipate that a similar approach can be applied to other endogenous metabolites to facilitate quantitative metabolomics studies.

  8. Integrated work-flow for quantitative metabolome profiling of plants, Peucedani Radix as a case.

    PubMed

    Song, Yuelin; Song, Qingqing; Liu, Yao; Li, Jun; Wan, Jian-Bo; Wang, Yitao; Jiang, Yong; Tu, Pengfei

    2017-02-08

    Universal acquisition of reliable information regarding the qualitative and quantitative properties of complicated matrices is the premise for the success of metabolomics study. Liquid chromatography-mass spectrometry (LC-MS) is now serving as a workhorse for metabolomics; however, LC-MS-based non-targeted metabolomics is suffering from some shortcomings, even some cutting-edge techniques have been introduced. Aiming to tackle, to some extent, the drawbacks of the conventional approaches, such as redundant information, detector saturation, low sensitivity, and inconstant signal number among different runs, herein, a novel and flexible work-flow consisting of three progressive steps was proposed to profile in depth the quantitative metabolome of plants. The roots of Peucedanum praeruptorum Dunn (Peucedani Radix, PR) that are rich in various coumarin isomers, were employed as a case study to verify the applicability. First, offline two dimensional LC-MS was utilized for in-depth detection of metabolites in a pooled PR extract namely universal metabolome standard (UMS). Second, mass fragmentation rules, notably concerning angular-type pyranocoumarins that are the primary chemical homologues in PR, and available databases were integrated for signal assignment and structural annotation. Third, optimum collision energy (OCE) as well as ion transition for multiple monitoring reaction measurement was online optimized with a reference compound-free strategy for each annotated component and large-scale relative quantification of all annotated components was accomplished by plotting calibration curves via serially diluting UMS. It is worthwhile to highlight that the potential of OCE for isomer discrimination was described and the linearity ranges of those primary ingredients were extended by suppressing their responses. The integrated workflow is expected to be qualified as a promising pipeline to clarify the quantitative metabolome of plants because it could not only

  9. Targeted metabolomic profiling in rat tissues reveals sex differences.

    PubMed

    Ruoppolo, Margherita; Caterino, Marianna; Albano, Lucia; Pecce, Rita; Di Girolamo, Maria Grazia; Crisci, Daniela; Costanzo, Michele; Milella, Luigi; Franconi, Flavia; Campesi, Ilaria

    2018-03-16

    Sex differences affect several diseases and are organ-and parameter-specific. In humans and animals, sex differences also influence the metabolism and homeostasis of amino acids and fatty acids, which are linked to the onset of diseases. Thus, the use of targeted metabolite profiles in tissues represents a powerful approach to examine the intermediary metabolism and evidence for any sex differences. To clarify the sex-specific activities of liver, heart and kidney tissues, we used targeted metabolomics, linear discriminant analysis (LDA), principal component analysis (PCA), cluster analysis and linear correlation models to evaluate sex and organ-specific differences in amino acids, free carnitine and acylcarnitine levels in male and female Sprague-Dawley rats. Several intra-sex differences affect tissues, indicating that metabolite profiles in rat hearts, livers and kidneys are organ-dependent. Amino acids and carnitine levels in rat hearts, livers and kidneys are affected by sex: male and female hearts show the greatest sexual dimorphism, both qualitatively and quantitatively. Finally, multivariate analysis confirmed the influence of sex on the metabolomics profiling. Our data demonstrate that the metabolomics approach together with a multivariate approach can capture the dynamics of physiological and pathological states, which are essential for explaining the basis of the sex differences observed in physiological and pathological conditions.

  10. Mass spectrometry as a quantitative tool in plant metabolomics

    PubMed Central

    Jorge, Tiago F.; Mata, Ana T.

    2016-01-01

    Metabolomics is a research field used to acquire comprehensive information on the composition of a metabolite pool to provide a functional screen of the cellular state. Studies of the plant metabolome include the analysis of a wide range of chemical species with very diverse physico-chemical properties, and therefore powerful analytical tools are required for the separation, characterization and quantification of this vast compound diversity present in plant matrices. In this review, challenges in the use of mass spectrometry (MS) as a quantitative tool in plant metabolomics experiments are discussed, and important criteria for the development and validation of MS-based analytical methods provided. This article is part of the themed issue ‘Quantitative mass spectrometry’. PMID:27644967

  11. Towards quantitative mass spectrometry-based metabolomics in microbial and mammalian systems.

    PubMed

    Kapoore, Rahul Vijay; Vaidyanathan, Seetharaman

    2016-10-28

    Metabolome analyses are a suite of analytical approaches that enable us to capture changes in the metabolome (small molecular weight components, typically less than 1500 Da) in biological systems. Mass spectrometry (MS) has been widely used for this purpose. The key challenge here is to be able to capture changes in a reproducible and reliant manner that is representative of the events that take place in vivo Typically, the analysis is carried out in vitro, by isolating the system and extracting the metabolome. MS-based approaches enable us to capture metabolomic changes with high sensitivity and resolution. When developing the technique for different biological systems, there are similarities in challenges and differences that are specific to the system under investigation. Here, we review some of the challenges in capturing quantitative changes in the metabolome with MS based approaches, primarily in microbial and mammalian systems.This article is part of the themed issue 'Quantitative mass spectrometry'. © 2016 The Author(s).

  12. Development and Evaluation of a Parallel Reaction Monitoring Strategy for Large-Scale Targeted Metabolomics Quantification.

    PubMed

    Zhou, Juntuo; Liu, Huiying; Liu, Yang; Liu, Jia; Zhao, Xuyang; Yin, Yuxin

    2016-04-19

    Recent advances in mass spectrometers which have yielded higher resolution and faster scanning speeds have expanded their application in metabolomics of diverse diseases. Using a quadrupole-Orbitrap LC-MS system, we developed an efficient large-scale quantitative method targeting 237 metabolites involved in various metabolic pathways using scheduled, parallel reaction monitoring (PRM). We assessed the dynamic range, linearity, reproducibility, and system suitability of the PRM assay by measuring concentration curves, biological samples, and clinical serum samples. The quantification performances of PRM and MS1-based assays in Q-Exactive were compared, and the MRM assay in QTRAP 6500 was also compared. The PRM assay monitoring 237 polar metabolites showed greater reproducibility and quantitative accuracy than MS1-based quantification and also showed greater flexibility in postacquisition assay refinement than the MRM assay in QTRAP 6500. We present a workflow for convenient PRM data processing using Skyline software which is free of charge. In this study we have established a reliable PRM methodology on a quadrupole-Orbitrap platform for evaluation of large-scale targeted metabolomics, which provides a new choice for basic and clinical metabolomics study.

  13. Metabolomics by Gas Chromatography-Mass Spectrometry: the combination of targeted and untargeted profiling

    PubMed Central

    Fiehn, Oliver

    2016-01-01

    Gas chromatography-mass spectrometry (GC-MS)-based metabolomics is ideal for identifying and quantitating small molecular metabolites (<650 daltons), including small acids, alcohols, hydroxyl acids, amino acids, sugars, fatty acids, sterols, catecholamines, drugs, and toxins, often using chemical derivatization to make these compounds volatile enough for gas chromatography. This unit shows that on GC-MS- based metabolomics easily allows integrating targeted assays for absolute quantification of specific metabolites with untargeted metabolomics to discover novel compounds. Complemented by database annotations using large spectral libraries and validated, standardized standard operating procedures, GC-MS can identify and semi-quantify over 200 compounds per study in human body fluids (e.g., plasma, urine or stool) samples. Deconvolution software enables detection of more than 300 additional unidentified signals that can be annotated through accurate mass instruments with appropriate data processing workflows, similar to liquid chromatography-MS untargeted profiling (LC-MS). Hence, GC-MS is a mature technology that not only uses classic detectors (‘quadrupole’) but also target mass spectrometers (‘triple quadrupole’) and accurate mass instruments (‘quadrupole-time of flight’). This unit covers the following aspects of GC-MS-based metabolomics: (i) sample preparation from mammalian samples, (ii) acquisition of data, (iii) quality control, and (iv) data processing. PMID:27038389

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bingol, Kerem

    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 NMRmore » 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.« less

  15. Exploring the Process of Energy Generation in Pathophysiology by Targeted Metabolomics: Performance of a Simple and Quantitative Method.

    PubMed

    Riera-Borrull, Marta; Rodríguez-Gallego, Esther; Hernández-Aguilera, Anna; Luciano, Fedra; Ras, Rosa; Cuyàs, Elisabet; Camps, Jordi; Segura-Carretero, Antonio; Menendez, Javier A; Joven, Jorge; Fernández-Arroyo, Salvador

    2016-01-01

    Abnormalities in mitochondrial metabolism and regulation of energy balance contribute to human diseases. The consequences of high fat and other nutrient intake, and the resulting acquired mitochondrial dysfunction, are essential to fully understand common disorders, including obesity, cancer, and atherosclerosis. To simultaneously and noninvasively measure and quantify indirect markers of mitochondrial function, we have developed a method based on gas chromatography coupled to quadrupole-time of flight mass spectrometry and an electron ionization interface, and validated the system using plasma from patients with peripheral artery disease, human cancer cells, and mouse tissues. This approach was used to increase sensibility in the measurement of a wide dynamic range and chemical diversity of multiple intermediate metabolites used in energy metabolism. We demonstrate that our targeted metabolomics method allows for quick and accurate identification and quantification of molecules, including the measurement of small yet significant biological changes in experimental samples. The apparently low process variability required for its performance in plasma, cell lysates, and tissues allowed a rapid identification of correlations between interconnected pathways. Our results suggest that delineating the process of energy generation by targeted metabolomics can be a valid surrogate for predicting mitochondrial dysfunction in biological samples. Importantly, when used in plasma, targeted metabolomics should be viewed as a robust and noninvasive source of biomarkers in specific pathophysiological scenarios.

  16. Exploring the Process of Energy Generation in Pathophysiology by Targeted Metabolomics: Performance of a Simple and Quantitative Method

    NASA Astrophysics Data System (ADS)

    Riera-Borrull, Marta; Rodríguez-Gallego, Esther; Hernández-Aguilera, Anna; Luciano, Fedra; Ras, Rosa; Cuyàs, Elisabet; Camps, Jordi; Segura-Carretero, Antonio; Menendez, Javier A.; Joven, Jorge; Fernández-Arroyo, Salvador

    2016-01-01

    Abnormalities in mitochondrial metabolism and regulation of energy balance contribute to human diseases. The consequences of high fat and other nutrient intake, and the resulting acquired mitochondrial dysfunction, are essential to fully understand common disorders, including obesity, cancer, and atherosclerosis. To simultaneously and noninvasively measure and quantify indirect markers of mitochondrial function, we have developed a method based on gas chromatography coupled to quadrupole-time of flight mass spectrometry and an electron ionization interface, and validated the system using plasma from patients with peripheral artery disease, human cancer cells, and mouse tissues. This approach was used to increase sensibility in the measurement of a wide dynamic range and chemical diversity of multiple intermediate metabolites used in energy metabolism. We demonstrate that our targeted metabolomics method allows for quick and accurate identification and quantification of molecules, including the measurement of small yet significant biological changes in experimental samples. The apparently low process variability required for its performance in plasma, cell lysates, and tissues allowed a rapid identification of correlations between interconnected pathways. Our results suggest that delineating the process of energy generation by targeted metabolomics can be a valid surrogate for predicting mitochondrial dysfunction in biological samples. Importantly, when used in plasma, targeted metabolomics should be viewed as a robust and noninvasive source of biomarkers in specific pathophysiological scenarios.

  17. The Human Serum Metabolome

    PubMed Central

    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

  18. Quantitative Metabolomics Reveals an Epigenetic Blueprint for Iron Acquisition in Uropathogenic Escherichia coli

    PubMed Central

    Henderson, Jeffrey P.; Crowley, Jan R.; Pinkner, Jerome S.; Walker, Jennifer N.; Tsukayama, Pablo; Stamm, Walter E.; Hooton, Thomas M.; Hultgren, Scott J.

    2009-01-01

    Bacterial pathogens are frequently distinguished by the presence of acquired genes associated with iron acquisition. The presence of specific siderophore receptor genes, however, does not reliably predict activity of the complex protein assemblies involved in synthesis and transport of these secondary metabolites. Here, we have developed a novel quantitative metabolomic approach based on stable isotope dilution to compare the complement of siderophores produced by Escherichia coli strains associated with intestinal colonization or urinary tract disease. Because uropathogenic E. coli are believed to reside in the gut microbiome prior to infection, we compared siderophore production between urinary and rectal isolates within individual patients with recurrent UTI. While all strains produced enterobactin, strong preferential expression of the siderophores yersiniabactin and salmochelin was observed among urinary strains. Conventional PCR genotyping of siderophore receptors was often insensitive to these differences. A linearized enterobactin siderophore was also identified as a product of strains with an active salmochelin gene cluster. These findings argue that qualitative and quantitative epi-genetic optimization occurs in the E. coli secondary metabolome among human uropathogens. Because the virulence-associated biosynthetic pathways are distinct from those associated with rectal colonization, these results suggest strategies for virulence-targeted therapies. PMID:19229321

  19. Amino acids in a targeted versus a non-targeted metabolomics LC-MS/MS assay. Are the results consistent?

    PubMed

    Klepacki, Jacek; Klawitter, Jost; Klawitter, Jelena; Karimpour-Fard, Anis; Thurman, Joshua; Ingle, Gordon; Patel, Dharmesh; Christians, Uwe

    2016-09-01

    The results of plasma amino acid patterns in samples from kidney transplant patients with good and impaired renal function using a targeted LC-MS/MS amino acid assay and a non-targeted metabolomics assay were compared. EDTA plasma samples were prospectively collected at baseline, 1, 2, 4 and 6months post-transplant (n=116 patients, n=398 samples). Each sample was analyzed using both a commercial amino acid LC-MS/MS assay and a non-targeted metabolomics assay also based on MS/MS ion transitions. The results of both assays were independently statistically analyzed to identify amino acids associated with estimated glomerular filtration rates using correlation and partial least squares-discriminant analysis. Although there was overlap between the results of the targeted and non-targeted metabolomics assays (tryptophan, 1-methyl histidine), there were also substantial inconsistencies, with the non-targeted assay resulting in more "hits" than the targeted assay. Without further verification of the hits detected by the non-targeted discovery assay, this would have led to different interpretation of the results. There were also false negative results when the non-targeted assay was used (hydroxy proline). Several of said discrepancies could be explained by loss of sensitivity during analytical runs for selected amino acids (serine and threonine), retention time shifts, signals above the range of linear detector response and integration of peaks not separated from background and interferences (aspartate) when the non-targeted metabolomics assay was used. Whenever assessment of a specific pathway such as amino acids is the focus of interest, a targeted seems preferable to a non-targeted metabolomics assay. Copyright © 2016. Published by Elsevier Inc.

  20. Multidimensional NMR approaches towards highly resolved, sensitive and high-throughput quantitative metabolomics.

    PubMed

    Marchand, Jérémy; Martineau, Estelle; Guitton, Yann; Dervilly-Pinel, Gaud; Giraudeau, Patrick

    2017-02-01

    Multi-dimensional NMR is an appealing approach for dealing with the challenging complexity of biological samples in metabolomics. This article describes how spectroscopists have recently challenged their imagination in order to make 2D NMR a powerful tool for quantitative metabolomics, based on innovative pulse sequences combined with meticulous analytical chemistry approaches. Clever time-saving strategies have also been explored to make 2D NMR a high-throughput tool for metabolomics, relying on alternative data acquisition schemes such as ultrafast NMR. Currently, much work is aimed at drastically boosting the NMR sensitivity thanks to hyperpolarisation techniques, which have been used in combination with fast acquisition methods and could greatly expand the application potential of NMR metabolomics. Copyright © 2016 Elsevier Ltd. All rights reserved.

  1. Mixture model normalization for non-targeted gas chromatography/mass spectrometry metabolomics data.

    PubMed

    Reisetter, Anna C; Muehlbauer, Michael J; Bain, James R; Nodzenski, Michael; Stevens, Robert D; Ilkayeva, Olga; Metzger, Boyd E; Newgard, Christopher B; Lowe, William L; Scholtens, Denise M

    2017-02-02

    Metabolomics offers a unique integrative perspective for health research, reflecting genetic and environmental contributions to disease-related phenotypes. Identifying robust associations in population-based or large-scale clinical studies demands large numbers of subjects and therefore sample batching for gas-chromatography/mass spectrometry (GC/MS) non-targeted assays. When run over weeks or months, technical noise due to batch and run-order threatens data interpretability. Application of existing normalization methods to metabolomics is challenged by unsatisfied modeling assumptions and, notably, failure to address batch-specific truncation of low abundance compounds. To curtail technical noise and make GC/MS metabolomics data amenable to analyses describing biologically relevant variability, we propose mixture model normalization (mixnorm) that accommodates truncated data and estimates per-metabolite batch and run-order effects using quality control samples. Mixnorm outperforms other approaches across many metrics, including improved correlation of non-targeted and targeted measurements and superior performance when metabolite detectability varies according to batch. For some metrics, particularly when truncation is less frequent for a metabolite, mean centering and median scaling demonstrate comparable performance to mixnorm. When quality control samples are systematically included in batches, mixnorm is uniquely suited to normalizing non-targeted GC/MS metabolomics data due to explicit accommodation of batch effects, run order and varying thresholds of detectability. Especially in large-scale studies, normalization is crucial for drawing accurate conclusions from non-targeted GC/MS metabolomics data.

  2. MRMPROBS: a data assessment and metabolite identification tool for large-scale multiple reaction monitoring based widely targeted metabolomics.

    PubMed

    Tsugawa, Hiroshi; Arita, Masanori; Kanazawa, Mitsuhiro; Ogiwara, Atsushi; Bamba, Takeshi; Fukusaki, Eiichiro

    2013-05-21

    We developed a new software program, MRMPROBS, for widely targeted metabolomics by using the large-scale multiple reaction monitoring (MRM) mode. The strategy became increasingly popular for the simultaneous analysis of up to several hundred metabolites at high sensitivity, selectivity, and quantitative capability. However, the traditional method of assessing measured metabolomics data without probabilistic criteria is not only time-consuming but is often subjective and makeshift work. Our program overcomes these problems by detecting and identifying metabolites automatically, by separating isomeric metabolites, and by removing background noise using a probabilistic score defined as the odds ratio from an optimized multivariate logistic regression model. Our software program also provides a user-friendly graphical interface to curate and organize data matrices and to apply principal component analyses and statistical tests. For a demonstration, we conducted a widely targeted metabolome analysis (152 metabolites) of propagating Saccharomyces cerevisiae measured at 15 time points by gas and liquid chromatography coupled to triple quadrupole mass spectrometry. MRMPROBS is a useful and practical tool for the assessment of large-scale MRM data available to any instrument or any experimental condition.

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

    PubMed Central

    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

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

    PubMed

    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.

  5. Advances in metabolome information retrieval: turning chemistry into biology. Part I: analytical chemistry of the metabolome.

    PubMed

    Tebani, Abdellah; Afonso, Carlos; Bekri, Soumeya

    2018-05-01

    Metabolites are small molecules produced by enzymatic reactions in a given organism. Metabolomics or metabolic phenotyping is a well-established omics aimed at comprehensively assessing metabolites in biological systems. These comprehensive analyses use analytical platforms, mainly nuclear magnetic resonance spectroscopy and mass spectrometry, along with associated separation methods to gather qualitative and quantitative data. Metabolomics holistically evaluates biological systems in an unbiased, data-driven approach that may ultimately support generation of hypotheses. The approach inherently allows the molecular characterization of a biological sample with regard to both internal (genetics) and environmental (exosome, microbiome) influences. Metabolomics workflows are based on whether the investigator knows a priori what kind of metabolites to assess. Thus, a targeted metabolomics approach is defined as a quantitative analysis (absolute concentrations are determined) or a semiquantitative analysis (relative intensities are determined) of a set of metabolites that are possibly linked to common chemical classes or a selected metabolic pathway. An untargeted metabolomics approach is a semiquantitative analysis of the largest possible number of metabolites contained in a biological sample. This is part I of a review intending to give an overview of the state of the art of major metabolic phenotyping technologies. Furthermore, their inherent analytical advantages and limits regarding experimental design, sample handling, standardization and workflow challenges are discussed.

  6. What computational non-targeted mass spectrometry-based metabolomics can gain from shotgun proteomics.

    PubMed

    Hamzeiy, Hamid; Cox, Jürgen

    2017-02-01

    Computational workflows for mass spectrometry-based shotgun proteomics and untargeted metabolomics share many steps. Despite the similarities, untargeted metabolomics is lagging behind in terms of reliable fully automated quantitative data analysis. We argue that metabolomics will strongly benefit from the adaptation of successful automated proteomics workflows to metabolomics. MaxQuant is a popular platform for proteomics data analysis and is widely considered to be superior in achieving high precursor mass accuracies through advanced nonlinear recalibration, usually leading to five to ten-fold better accuracy in complex LC-MS/MS runs. This translates to a sharp decrease in the number of peptide candidates per measured feature, thereby strongly improving the coverage of identified peptides. We argue that similar strategies can be applied to untargeted metabolomics, leading to equivalent improvements in metabolite identification. Copyright © 2016 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  7. Fully Bayesian Analysis of High-throughput Targeted Metabolomics Assays

    EPA Science Inventory

    High-throughput metabolomic assays that allow simultaneous targeted screening of hundreds of metabolites have recently become available in kit form. Such assays provide a window into understanding changes to biochemical pathways due to chemical exposure or disease, and are usefu...

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

    PubMed

    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 < 0.001 after Bonferroni correction). Moreover, a combination of 2-isopropylmalic acid and betaine strongly discriminated between children with asthma (2-isopropylmalic acid ≤ 13 077 normalized counts/second) and controls (2-isopropylmalic acid > 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

  9. Chiral PCB 91 and 149 Toxicity Testing in Embryo and Larvae (Danio rerio): Application of Targeted Metabolomics via UPLC-MS/MS

    NASA Astrophysics Data System (ADS)

    Chai, Tingting; Cui, Feng; Yin, Zhiqiang; Yang, Yang; Qiu, Jing; Wang, Chengju

    2016-09-01

    In this study, we aimed to investigate the dysfunction of zebrafish embryos and larvae induced by rac-/(+)-/(-)- PCB91 and rac-/(-)-/(+)- PCB149. UPLC-MS/MS (Ultra-performance liquid chromatography coupled with mass spectrometry) was employed to perform targeted metabolomics analysis, including the quantification of 22 amino acids and the semi-quantitation of 22 other metabolites. Stereoselective changes in target metabolites were observed in embryos and larvae after exposure to chiral PCB91 and PCB149, respectively. In addition, statistical analyses, including PCA and PLS-DA, combined with targeted metabolomics were conducted to identify the characteristic metabolites and the affected pathways. Most of the unique metabolites in embryos and larvae after PCB91/149 exposure were amino acids, and the affected pathways for zebrafish in the developmental stage were metabolic pathways. The stereoselective effects of PCB91/149 on the metabolic pathways of zebrafish embryos and larvae suggest that chiral PCB91/149 exposure has stereoselective toxicity on the developmental stages of zebrafish.

  10. iMet-Q: A User-Friendly Tool for Label-Free Metabolomics Quantitation Using Dynamic Peak-Width Determination

    PubMed Central

    Chang, Hui-Yin; Chen, Ching-Tai; Lih, T. Mamie; Lynn, Ke-Shiuan; Juo, Chiun-Gung; Hsu, Wen-Lian; Sung, Ting-Yi

    2016-01-01

    Efficient and accurate quantitation of metabolites from LC-MS data has become an important topic. Here we present an automated tool, called iMet-Q (intelligent Metabolomic Quantitation), for label-free metabolomics quantitation from high-throughput MS1 data. By performing peak detection and peak alignment, iMet-Q provides a summary of quantitation results and reports ion abundance at both replicate level and sample level. Furthermore, it gives the charge states and isotope ratios of detected metabolite peaks to facilitate metabolite identification. An in-house standard mixture and a public Arabidopsis metabolome data set were analyzed by iMet-Q. Three public quantitation tools, including XCMS, MetAlign, and MZmine 2, were used for performance comparison. From the mixture data set, seven standard metabolites were detected by the four quantitation tools, for which iMet-Q had a smaller quantitation error of 12% in both profile and centroid data sets. Our tool also correctly determined the charge states of seven standard metabolites. By searching the mass values for those standard metabolites against Human Metabolome Database, we obtained a total of 183 metabolite candidates. With the isotope ratios calculated by iMet-Q, 49% (89 out of 183) metabolite candidates were filtered out. From the public Arabidopsis data set reported with two internal standards and 167 elucidated metabolites, iMet-Q detected all of the peaks corresponding to the internal standards and 167 metabolites. Meanwhile, our tool had small abundance variation (≤0.19) when quantifying the two internal standards and had higher abundance correlation (≥0.92) when quantifying the 167 metabolites. iMet-Q provides user-friendly interfaces and is publicly available for download at http://ms.iis.sinica.edu.tw/comics/Software_iMet-Q.html. PMID:26784691

  11. Integrated and global pseudotargeted metabolomics strategy applied to screening for quality control markers of Citrus TCMs.

    PubMed

    Shu, Yisong; Liu, Zhenli; Zhao, Siyu; Song, Zhiqian; He, Dan; Wang, Menglei; Zeng, Honglian; Lu, Cheng; Lu, Aiping; Liu, Yuanyan

    2017-08-01

    Traditional Chinese medicine (TCM) exerts its therapeutic effect in a holistic fashion with the synergistic function of multiple characteristic constituents. The holism philosophy of TCM is coincident with global and systematic theories of metabolomics. The proposed pseudotargeted metabolomics methodologies were employed for the establishment of reliable quality control markers for use in the screening strategy of TCMs. Pseudotargeted metabolomics integrates the advantages of both targeted and untargeted methods. In the present study, targeted metabolomics equipped with the gold standard RRLC-QqQ-MS method was employed for in vivo quantitative plasma pharmacochemistry study of characteristic prototypic constituents. Meanwhile, untargeted metabolomics using UHPLC-QE Orbitrap HRMS with better specificity and selectivity was employed for identification of untargeted metabolites in the complex plasma matrix. In all, 32 prototypic metabolites were quantitatively determined, and 66 biotransformed metabolites were convincingly identified after being orally administered with standard extracts of four labeled Citrus TCMs. The global absorption and metabolism process of complex TCMs was depicted in a systematic manner.

  12. Targeting of the hydrophobic metabolome by pathogens.

    PubMed

    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.

  13. A Strategy for Sensitive, Large Scale Quantitative Metabolomics

    PubMed Central

    Liu, Xiaojing; Ser, Zheng; Cluntun, Ahmad A.; Mentch, Samantha J.; Locasale, Jason W.

    2014-01-01

    Metabolite profiling has been a valuable asset in the study of metabolism in health and disease. However, current platforms have different limiting factors, such as labor intensive sample preparations, low detection limits, slow scan speeds, intensive method optimization for each metabolite, and the inability to measure both positively and negatively charged ions in single experiments. Therefore, a novel metabolomics protocol could advance metabolomics studies. Amide-based hydrophilic chromatography enables polar metabolite analysis without any chemical derivatization. High resolution MS using the Q-Exactive (QE-MS) has improved ion optics, increased scan speeds (256 msec at resolution 70,000), and has the capability of carrying out positive/negative switching. Using a cold methanol extraction strategy, and coupling an amide column with QE-MS enables robust detection of 168 targeted polar metabolites and thousands of additional features simultaneously.  Data processing is carried out with commercially available software in a highly efficient way, and unknown features extracted from the mass spectra can be queried in databases. PMID:24894601

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

    PubMed

    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.

  15. Quantitative Metabolome Analysis Based on Chromatographic Peak Reconstruction in Chemical Isotope Labeling Liquid Chromatography Mass Spectrometry.

    PubMed

    Huan, Tao; Li, Liang

    2015-07-21

    Generating precise and accurate quantitative information on metabolomic changes in comparative samples is important for metabolomics research where technical variations in the metabolomic data should be minimized in order to reveal biological changes. We report a method and software program, IsoMS-Quant, for extracting quantitative information from a metabolomic data set generated by chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS). Unlike previous work of relying on mass spectral peak ratio of the highest intensity peak pair to measure relative quantity difference of a differentially labeled metabolite, this new program reconstructs the chromatographic peaks of the light- and heavy-labeled metabolite pair and then calculates the ratio of their peak areas to represent the relative concentration difference in two comparative samples. Using chromatographic peaks to perform relative quantification is shown to be more precise and accurate. IsoMS-Quant is integrated with IsoMS for picking peak pairs and Zero-fill for retrieving missing peak pairs in the initial peak pairs table generated by IsoMS to form a complete tool for processing CIL LC-MS data. This program can be freely downloaded from the www.MyCompoundID.org web site for noncommercial use.

  16. Elucidating dynamic metabolic physiology through network integration of quantitative time-course metabolomics

    DOE PAGES

    Bordbar, Aarash; Yurkovich, James T.; Paglia, Giuseppe; ...

    2017-04-07

    In this study, the increasing availability of metabolomics data necessitates novel methods for deeper data analysis and interpretation. We present a flux balance analysis method that allows for the computation of dynamic intracellular metabolic changes at the cellular scale through integration of time-course absolute quantitative metabolomics. This approach, termed “unsteady-state flux balance analysis” (uFBA), is applied to four cellular systems: three dynamic and one steady-state as a negative control. uFBA and FBA predictions are contrasted, and uFBA is found to be more accurate in predicting dynamic metabolic flux states for red blood cells, platelets, and Saccharomyces cerevisiae. Notably, only uFBAmore » predicts that stored red blood cells metabolize TCA intermediates to regenerate important cofactors, such as ATP, NADH, and NADPH. These pathway usage predictions were subsequently validated through 13C isotopic labeling and metabolic flux analysis in stored red blood cells. Utilizing time-course metabolomics data, uFBA provides an accurate method to predict metabolic physiology at the cellular scale for dynamic systems.« less

  17. Elucidating dynamic metabolic physiology through network integration of quantitative time-course metabolomics

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Bordbar, Aarash; Yurkovich, James T.; Paglia, Giuseppe

    In this study, the increasing availability of metabolomics data necessitates novel methods for deeper data analysis and interpretation. We present a flux balance analysis method that allows for the computation of dynamic intracellular metabolic changes at the cellular scale through integration of time-course absolute quantitative metabolomics. This approach, termed “unsteady-state flux balance analysis” (uFBA), is applied to four cellular systems: three dynamic and one steady-state as a negative control. uFBA and FBA predictions are contrasted, and uFBA is found to be more accurate in predicting dynamic metabolic flux states for red blood cells, platelets, and Saccharomyces cerevisiae. Notably, only uFBAmore » predicts that stored red blood cells metabolize TCA intermediates to regenerate important cofactors, such as ATP, NADH, and NADPH. These pathway usage predictions were subsequently validated through 13C isotopic labeling and metabolic flux analysis in stored red blood cells. Utilizing time-course metabolomics data, uFBA provides an accurate method to predict metabolic physiology at the cellular scale for dynamic systems.« less

  18. Non-targeted plasma metabolome of early and late lactation gilts

    USDA-ARS?s Scientific Manuscript database

    Female pigs nursing their first litter (first-parity gilts) have increased energy requirements not only to support their piglets, but they themselves are still maturing. Non-targeted plasma metabolomics were used to investigate the differences between (1) post-farrowing and weaning (early or late l...

  19. Metabolomics through the lens of precision cardiovascular medicine.

    PubMed

    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.

  20. Mass spectrometry-based metabolomics: Targeting the crosstalk between gut microbiota and brain in neurodegenerative disorders.

    PubMed

    Luan, Hemi; Wang, Xian; Cai, Zongwei

    2017-11-12

    Metabolomics seeks to take a "snapshot" in a time of the levels, activities, regulation and interactions of all small molecule metabolites in response to a biological system with genetic or environmental changes. The emerging development in mass spectrometry technologies has shown promise in the discovery and quantitation of neuroactive small molecule metabolites associated with gut microbiota and brain. Significant progress has been made recently in the characterization of intermediate role of small molecule metabolites linked to neural development and neurodegenerative disorder, showing its potential in understanding the crosstalk between gut microbiota and the host brain. More evidence reveals that small molecule metabolites may play a critical role in mediating microbial effects on neurotransmission and disease development. Mass spectrometry-based metabolomics is uniquely suitable for obtaining the metabolic signals in bidirectional communication between gut microbiota and brain. In this review, we summarized major mass spectrometry technologies including liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and imaging mass spectrometry for metabolomics studies of neurodegenerative disorders. We also reviewed the recent advances in the identification of new metabolites by mass spectrometry and metabolic pathways involved in the connection of intestinal microbiota and brain. These metabolic pathways allowed the microbiota to impact the regular function of the brain, which can in turn affect the composition of microbiota via the neurotransmitter substances. The dysfunctional interaction of this crosstalk connects neurodegenerative diseases, including Parkinson's disease, Alzheimer's disease and Huntington's disease. The mass spectrometry-based metabolomics analysis provides information for targeting dysfunctional pathways of small molecule metabolites in the development of the neurodegenerative diseases, which may be valuable for the

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

    PubMed Central

    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

  2. Mortality prediction in patients with severe septic shock: a pilot study using a target metabolomics approach.

    PubMed

    Ferrario, Manuela; Cambiaghi, Alice; Brunelli, Laura; Giordano, Silvia; Caironi, Pietro; Guatteri, Luca; Raimondi, Ferdinando; Gattinoni, Luciano; Latini, Roberto; Masson, Serge; Ristagno, Giuseppe; Pastorelli, Roberta

    2016-02-05

    Septic shock remains a major problem in Intensive Care Unit, with high lethality and high-risk second lines treatments. In this preliminary retrospective investigation we examined plasma metabolome and clinical features in a subset of 20 patients with severe septic shock (SOFA score >8), enrolled in the multicenter Albumin Italian Outcome Sepsis study (ALBIOS, NCT00707122). Our purpose was to evaluate the changes of circulating metabolites in relation to mortality as a pilot study to be extended in a larger cohort. Patients were analyzed according to their 28-days and 90-days mortality. Metabolites were measured using a targeted mass spectrometry-based quantitative metabolomic approach that included acylcarnitines, aminoacids, biogenic amines, glycerophospholipids, sphingolipids, and sugars. Data-mining techniques were applied to evaluate the association of metabolites with mortality. Low unsaturated long-chain phosphatidylcholines and lysophosphatidylcholines species were associated with long-term survival (90-days) together with circulating kynurenine. Moreover, a decrease of these glycerophospholipids was associated to the event at 28-days and 90-days in combination with clinical variables such as cardiovascular SOFA score (28-day mortality model) or renal replacement therapy (90-day mortality model). Early changes in the plasma levels of both lipid species and kynurenine associated with mortality have potential implications for early intervention and discovering new target therapy.

  3. Mortality prediction in patients with severe septic shock: a pilot study using a target metabolomics approach

    PubMed Central

    Ferrario, Manuela; Cambiaghi, Alice; Brunelli, Laura; Giordano, Silvia; Caironi, Pietro; Guatteri, Luca; Raimondi, Ferdinando; Gattinoni, Luciano; Latini, Roberto; Masson, Serge; Ristagno, Giuseppe; Pastorelli, Roberta

    2016-01-01

    Septic shock remains a major problem in Intensive Care Unit, with high lethality and high-risk second lines treatments. In this preliminary retrospective investigation we examined plasma metabolome and clinical features in a subset of 20 patients with severe septic shock (SOFA score >8), enrolled in the multicenter Albumin Italian Outcome Sepsis study (ALBIOS, NCT00707122). Our purpose was to evaluate the changes of circulating metabolites in relation to mortality as a pilot study to be extended in a larger cohort. Patients were analyzed according to their 28-days and 90-days mortality. Metabolites were measured using a targeted mass spectrometry-based quantitative metabolomic approach that included acylcarnitines, aminoacids, biogenic amines, glycerophospholipids, sphingolipids, and sugars. Data-mining techniques were applied to evaluate the association of metabolites with mortality. Low unsaturated long-chain phosphatidylcholines and lysophosphatidylcholines species were associated with long-term survival (90-days) together with circulating kynurenine. Moreover, a decrease of these glycerophospholipids was associated to the event at 28-days and 90-days in combination with clinical variables such as cardiovascular SOFA score (28-day mortality model) or renal replacement therapy (90-day mortality model). Early changes in the plasma levels of both lipid species and kynurenine associated with mortality have potential implications for early intervention and discovering new target therapy. PMID:26847922

  4. Combining a nontargeted and targeted metabolomics approach to identify metabolic pathways significantly altered in polycystic ovary syndrome.

    PubMed

    Chang, Alice Y; Lalia, Antigoni Z; Jenkins, Gregory D; Dutta, Tumpa; Carter, Rickey E; Singh, Ravinder J; Nair, K Sreekumaran

    2017-06-01

    Polycystic ovary syndrome (PCOS) is a condition of androgen excess and chronic anovulation frequently associated with insulin resistance. We combined a nontargeted and targeted metabolomics approach to identify pathways and metabolites that distinguished PCOS from metabolic syndrome (MetS). Twenty obese women with PCOS were compared with 18 obese women without PCOS. Both groups met criteria for MetS but could not have diabetes mellitus or take medications that treat PCOS or affect lipids or insulin sensitivity. Insulin sensitivity was derived from the frequently sampled intravenous glucose tolerance test. A nontargeted metabolomics approach was performed on fasting plasma samples to identify differentially expressed metabolites, which were further evaluated by principal component and pathway enrichment analysis. Quantitative targeted metabolomics was then applied on candidate metabolites. Measured metabolites were tested for associations with PCOS and clinical variables by logistic and linear regression analyses. This multiethnic, obese sample was matched by age (PCOS, 37±6; MetS, 40±6years) and body mass index (BMI) (PCOS, 34.6±5.1; MetS, 33.7±5.2kg/m 2 ). Principal component analysis of the nontargeted metabolomics data showed distinct group separation of PCOS from MetS controls. From the subset of 385 differentially expressed metabolites, 22% were identified by accurate mass, resulting in 19 canonical pathways significantly altered in PCOS, including amino acid, lipid, steroid, carbohydrate, and vitamin D metabolism. Targeted metabolomics identified many essential amino acids, including branched-chain amino acids (BCAA) that were elevated in PCOS compared with MetS. PCOS was most associated with BCAA (P=.02), essential amino acids (P=.03), the essential amino acid lysine (P=.02), and the lysine metabolite α-aminoadipic acid (P=.02) in models adjusted for surrogate variables representing technical variation in metabolites. No significant differences between

  5. Combining a Nontargeted and Targeted Metabolomics Approach to Identify Metabolic Pathways Significantly Altered in Polycystic Ovary Syndrome

    PubMed Central

    Chang, Alice Y.; Lalia, Antigoni Z.; Jenkins, Gregory D.; Dutta, Tumpa; Carter, Rickey E.; Singh, Ravinder J.; Sreekumaran Nair, K.

    2017-01-01

    Objective Polycystic ovary syndrome (PCOS) is a condition of androgen excess and chronic anovulation frequently associated with insulin resistance. We combined a nontargeted and targeted metabolomics approach to identify pathways and metabolites that distinguished PCOS from metabolic syndrome (MetS). Methods Twenty obese women with PCOS were compared with 18 obese women without PCOS. Both groups met criteria for MetS but could not have diabetes mellitus or take medications that treat PCOS or affect lipids or insulin sensitivity. Insulin sensitivity was derived from the frequently sampled intravenous glucose tolerance test. A nontargeted metabolomics approach was performed on fasting plasma samples to identify differentially expressed metabolites, which were further evaluated by principal component and pathway enrichment analysis. Quantitative targeted metabolomics was then applied on candidate metabolites. Measured metabolites were tested for associations with PCOS and clinical variables by logistic and linear regression analyses. Results This multiethnic, obese sample was matched by age (PCOS, 37 ± 6; MetS, 40 ± 6 years) and body mass index (BMI) (PCOS, 34.6 ± 5.1; MetS, 33.7 ± 5.2 kg/m2). Principal component analysis of the nontargeted metabolomics data showed distinct group separation of PCOS from MetS controls. From the subset of 385 differentially expressed metabolites, 22% were identified by accurate mass, resulting in 19 canonical pathways significantly altered in PCOS, including amino acid, lipid, steroid, carbohydrate, and vitamin D metabolism. Targeted metabolomics identified many essential amino acids, including branched-chain amino acids (BCAA) that were elevated in PCOS compared with MetS. PCOS was most associated with BCAA (P = .02), essential amino acids (P = .03), the essential amino acid lysine (P = .02), and the lysine metabolite α-aminoadipic acid (P = .02) in models adjusted for surrogate variables representing technical variation in

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

    PubMed Central

    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

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

    PubMed

    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.

  8. Metabolomics Reveals Target and Off-Target Toxicities of a Model Organophosphate Pesticide to Roach (Rutilus rutilus): Implications for Biomonitoring

    PubMed Central

    2011-01-01

    The ability of targeted and nontargeted metabolomics to discover chronic ecotoxicological effects is largely unexplored. Fenitrothion, an organophosphate pesticide, is categorized as a “red list” pollutant, being particularly hazardous to aquatic life. It acts primarily as a cholinesterase inhibitor, but evidence suggests it can also act as an androgen receptor antagonist. Whole-organism fenitrothion-induced toxicity is well-established, but information regarding target and off-target molecular toxicities is limited. Here we study the molecular responses of male roach (Rutilus rutilus) exposed to fenitrothion, including environmentally realistic concentrations, for 28 days. Acetylcholine was assessed in brain; steroid metabolism was measured in testes and plasma; and NMR and mass spectrometry-based metabolomics were conducted on testes and liver to discover off-target toxicity. O-demethylation was confirmed as a major route of pesticide degradation. Fenitrothion significantly depleted acetylcholine, confirming its primary mode of action, and 11-ketotestosterone in plasma and cortisone in testes, showing disruption of steroid metabolism. Metabolomics revealed significant perturbations to the hepatic phosphagen system and previously undocumented effects on phenylalanine metabolism in liver and testes. On the basis of several unexpected molecular responses that were opposite to the anticipated acute toxicity, we propose that chronic pesticide exposure induces an adapting phenotype in roach, which may have considerable implications for interpreting molecular biomarker responses in field-sampled fish. PMID:21410251

  9. Metabolomics relative quantitation with mass spectrometry using chemical derivatization and isotope labeling

    DOE PAGES

    O'Maille, Grace; Go, Eden P.; Hoang, Linh; ...

    2008-01-01

    Comprehensive detection and quantitation of metabolites from a biological source constitute the major challenges of current metabolomics research. Two chemical derivatization methodologies, butylation and amination, were applied to human serum for ionization enhancement of a broad spectrum of metabolite classes, including steroids and amino acids. LC-ESI-MS analysis of the derivatized serum samples provided a significant signal elevation across the total ion chromatogram to over a 100-fold increase in ionization efficiency. It was also demonstrated that derivatization combined with isotopically labeled reagents facilitated the relative quantitation of derivatized metabolites from individual as well as pooled samples.

  10. Quantitative metabolomics of photoreceptor degeneration and the effects of stem cell-derived retinal pigment epithelium transplantation

    PubMed Central

    Wang, Junhua; Westenskow, Peter D.; Fang, Mingliang; Friedlander, Martin

    2016-01-01

    Photoreceptor degeneration is characteristic of vision-threatening diseases including age-related macular degeneration. Photoreceptors are metabolically demanding cells in the retina, but specific details about their metabolic behaviours are unresolved. The quantitative metabolomics of retinal degeneration could provide valuable insights and inform future therapies. Here, we determined the metabolomic ‘fingerprint’ of healthy and dystrophic retinas in rat models using optimized metabolite extraction techniques. A number of classes of metabolites were consistently dysregulated during degeneration: vitamin A analogues, fatty acid amides, long-chain polyunsaturated fatty acids, acyl carnitines and several phospholipid species. For the first time, a distinct temporal trend of several important metabolites including DHA (4Z,7Z,10Z,13Z,16Z,19Z-docosahexaenoic acid), all-trans-retinal and its toxic end-product N-retinyl-N-retinylidene-ethanolamine were observed between healthy and dystrophic retinas. In this study, metabolomics was further used to determine the temporal effects of the therapeutic intervention of grafting stem cell-derived retinal pigment epithelium (RPE) in dystrophic retinas, which significantly prevented photoreceptor atrophy in our previous studies. The result revealed that lipid levels such as phosphatidylethanolamine in eyes were restored in those animals receiving the RPE grafts. In conclusion, this study provides insight into the metabolomics of retinal degeneration, and further understanding of the efficacy of RPE transplantation. This article is part of the themed issue ‘Quantitative mass spectrometry’. PMID:27644974

  11. Development of isotope labeling liquid chromatography mass spectrometry for mouse urine metabolomics: quantitative metabolomic study of transgenic mice related to Alzheimer's disease.

    PubMed

    Peng, Jun; Guo, Kevin; Xia, Jianguo; Zhou, Jianjun; Yang, Jing; Westaway, David; Wishart, David S; Li, Liang

    2014-10-03

    Because of a limited volume of urine that can be collected from a mouse, it is very difficult to apply the common strategy of using multiple analytical techniques to analyze the metabolites to increase the metabolome coverage for mouse urine metabolomics. We report an enabling method based on differential isotope labeling liquid chromatography mass spectrometry (LC-MS) for relative quantification of over 950 putative metabolites using 20 μL of urine as the starting material. The workflow involves aliquoting 10 μL of an individual urine sample for ¹²C-dansylation labeling that target amines and phenols. Another 10 μL of aliquot was taken from each sample to generate a pooled sample that was subjected to ¹³C-dansylation labeling. The ¹²C-labeled individual sample was mixed with an equal volume of the ¹³C-labeled pooled sample. The mixture was then analyzed by LC-MS to generate information on metabolite concentration differences among different individual samples. The interday repeatability for the LC-MS runs was assessed, and the median relative standard deviation over 4 days was 5.0%. This workflow was then applied to a metabolomic biomarker discovery study using urine samples obtained from the TgCRND8 mouse model of early onset familial Alzheimer's disease (FAD) throughout the course of their pathological deposition of beta amyloid (Aβ). It was showed that there was a distinct metabolomic separation between the AD prone mice and the wild type (control) group. As early as 15-17 weeks of age (presymptomatic), metabolomic differences were observed between the two groups, and after the age of 25 weeks the metabolomic alterations became more pronounced. The metabolomic changes at different ages corroborated well with the phenotype changes in this transgenic mice model. Several useful candidate biomarkers including methionine, desaminotyrosine, taurine, N1-acetylspermidine, and 5-hydroxyindoleacetic acid were identified. Some of them were found in previous

  12. Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis.

    PubMed

    Xia, Jianguo; Wishart, David S

    2016-09-07

    MetaboAnalyst (http://www.metaboanalyst.ca) is a comprehensive Web application for metabolomic data analysis and interpretation. MetaboAnalyst handles most of the common metabolomic data types from most kinds of metabolomics platforms (MS and NMR) for most kinds of metabolomics experiments (targeted, untargeted, quantitative). In addition to providing a variety of data processing and normalization procedures, MetaboAnalyst also supports a number of data analysis and data visualization tasks using a range of univariate, multivariate methods such as PCA (principal component analysis), PLS-DA (partial least squares discriminant analysis), heatmap clustering and machine learning methods. MetaboAnalyst also offers a variety of tools for metabolomic data interpretation including MSEA (metabolite set enrichment analysis), MetPA (metabolite pathway analysis), and biomarker selection via ROC (receiver operating characteristic) curve analysis, as well as time series and power analysis. This unit provides an overview of the main functional modules and the general workflow of the latest version of MetaboAnalyst (MetaboAnalyst 3.0), followed by eight detailed protocols. © 2016 by John Wiley & Sons, Inc. Copyright © 2016 John Wiley & Sons, Inc.

  13. Development of Chemical Isotope Labeling LC-MS for Milk Metabolomics: Comprehensive and Quantitative Profiling of the Amine/Phenol Submetabolome.

    PubMed

    Mung, Dorothea; Li, Liang

    2017-04-18

    Milk is a complex sample containing a variety of proteins, lipids, and metabolites. Studying the milk metabolome represents an important application of metabolomics in the general area of nutritional research. However, comprehensive and quantitative analysis of milk metabolites is a challenging task due to the wide range of variations in chemical/physical properties and concentrations of these metabolites. We report an analytical workflow for in-depth profiling of the milk metabolome based on chemical isotope labeling (CIL) and liquid chromatography mass spectrometry (LC-MS) with a focus of using dansylation labeling to target the amine/phenol submetabolome. An optimal sample preparation method, including the use of methanol at a 3:1 ratio of solvent to milk for protein precipitation and dichloromethane for lipid removal, was developed to detect and quantify as many metabolites as possible. This workflow was found to be generally applicable to profile milk metabolomes of different species (cow, goat, and human) and types. Results from experimental replicate analysis (n = 5) of 1:1, 2:1, and 1:2 12 C-/ 13 C-labeled cow milk samples showed that 95.7%, 94.3%, and 93.2% of peak pairs, respectively, had ratio values within ±50% accuracy range and 90.7%, 92.6%, and 90.8% peak pairs had RSD values of less than 20%. In the metabolomic analysis of 36 samples from different categories of cow milk (brands, batches, and fat percentages) with experimental triplicates, a total of 7104 peak pairs or metabolites could be detected with an average of 4573 ± 505 (n = 108) pairs detected per LC-MS run. Among them, 3820 peak pairs were commonly detected in over 80% of the samples with 70 metabolites positively identified by mass and retention time matches to the dansyl standard library and 2988 pairs with their masses matched to the human metabolome libraries. This unprecedentedly high coverage of the amine/phenol submetabolome illustrates the complexity of the milk metabolome. Since

  14. Biodiversity in targeted metabolomics analysis of filamentous fungal pathogens by 1H NMR-based studies.

    PubMed

    Ząbek, Adam; Klimek-Ochab, Magdalena; Jawień, Ewa; Młynarz, Piotr

    2017-07-01

    The taxonomical classification among fungi kingdom in the last decades was evolved. In this work the targeted metabolomics study based on 1 H NMR spectroscopy combined with chemometrics tools was reported to be useful for differentiation of three model of fungal strains, which represent various genus of Ascomycota (Aspergillus pallidofulvus, Fusarium oxysporum, Geotrichum candidum) were selected in order to perform metabolomics studies. Each tested species, revealed specific metabolic profile of primary endo-metabolites. The species of A. pallidofulvus is represented by the highest concentration of glycerol, glucitol and Unk5. While, F. oxysporum species is characterised by increased level of propylene glycol, ethanol, 4-aminobutyrate, succinate, xylose, Unk1 and Unk4. In G. candidum, 3-methyl-2-oxovalerate, glutamate, pyruvate, glutamine and citrate were elevated. Additionally, a detailed analysis of metabolic changes among A. pallidofulvus, F. oxysporum and G. candidum showed that A. pallidofulvus seems to be the most pathogenic fungi. The obtained results demonstrated that targeted metabolomics analysis could be utilized in the future as a supporting taxonomical tool for currently methods.

  15. Informatics for Metabolomics.

    PubMed

    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.

  16. Quantitative metabolomics of the thermophilic methylotroph Bacillus methanolicus.

    PubMed

    Carnicer, Marc; Vieira, Gilles; Brautaset, Trygve; Portais, Jean-Charles; Heux, Stephanie

    2016-06-01

    The gram-positive bacterium Bacillus methanolicus MGA3 is a promising candidate for methanol-based biotechnologies. Accurate determination of intracellular metabolites is crucial for engineering this bacteria into an efficient microbial cell factory. Due to the diversity of chemical and cell properties, an experimental protocol validated on B. methanolicus is needed. Here a systematic evaluation of different techniques for establishing a reliable basis for metabolome investigations is presented. Metabolome analysis was focused on metabolites closely linked with B. methanolicus central methanol metabolism. As an alternative to cold solvent based procedures, a solvent-free quenching strategy using stainless steel beads cooled to -20 °C was assessed. The precision, the consistency of the measurements, and the extent of metabolite leakage from quenched cells were evaluated in procedures with and without cell separation. The most accurate and reliable performance was provided by the method without cell separation, as significant metabolite leakage occurred in the procedures based on fast filtration. As a biological test case, the best protocol was used to assess the metabolome of B. methanolicus grown in chemostat on methanol at two different growth rates and its validity was demonstrated. The presented protocol is a first and helpful step towards developing reliable metabolomics data for thermophilic methylotroph B. methanolicus. This will definitely help for designing an efficient methylotrophic cell factory.

  17. Targeted metabolomics profiles are strongly correlated with nutritional patterns in women.

    PubMed

    Menni, Cristina; Zhai, Guangju; Macgregor, Alexander; Prehn, Cornelia; Römisch-Margl, Werner; Suhre, Karsten; Adamski, Jerzy; Cassidy, Aedin; Illig, Thomas; Spector, Tim D; Valdes, Ana M

    2013-04-01

    Nutrition plays an important role in human metabolism and health. Metabolomics is a promising tool for clinical, genetic and nutritional studies. A key question is to what extent metabolomic profiles reflect nutritional patterns in an epidemiological setting. We assessed the relationship between metabolomic profiles and nutritional intake in women from a large cross-sectional community study. Food frequency questionnaires (FFQs) were applied to 1,003 women from the TwinsUK cohort with targeted metabolomic analyses of serum samples using the Biocrates Absolute-IDQ™ Kit p150 (163 metabolites). We analyzed seven nutritional parameters: coffee intake, garlic intake and nutritional scores derived from the FFQs summarizing fruit and vegetable intake, alcohol intake, meat intake, hypo-caloric dieting and a "traditional English" diet. We studied the correlation between metabolite levels and dietary intake patterns in the larger population and identified for each trait between 14 and 20 independent monozygotic twins pairs discordant for nutritional intake and replicated results in this set. Results from both analyses were then meta-analyzed. For the metabolites associated with nutritional patterns, we calculated heritability using structural equation modelling. 42 metabolite nutrient intake associations were statistically significant in the discovery samples (Bonferroni P  < 4 × 10 -5 ) and 11 metabolite nutrient intake associations remained significant after validation. We found the strongest associations for fruit and vegetables intake and a glycerophospholipid (Phosphatidylcholine diacyl C38:6, P  = 1.39 × 10 -9 ) and a sphingolipid (Sphingomyeline C26:1, P  = 6.95 × 10 -13 ). We also found significant associations for coffee (confirming a previous association with C10 reported in an independent study), garlic intake and hypo-caloric dieting. Using the twin study design we find that two thirds the metabolites associated with nutritional patterns have a

  18. Application of Targeted Metabolomics to Investigate Optimum Growing Conditions to Enhance Bioactive Content of Strawberry.

    PubMed

    Akhatou, Ikram; Sayago, Ana; González-Domínguez, Raúl; Fernández-Recamales, Ángeles

    2017-11-01

    A simple, sensitive, and rapid assay based on liquid chromatography coupled to tandem mass spectrometry was designed for simultaneous quantitation of secondary metabolites in order to investigate the influence of variety and agronomic conditions on the biosynthesis of bioactive compounds in strawberry. For this purpose, strawberries belonging to three varieties with different sensitivity to environmental conditions ('Camarosa', 'Festival', 'Palomar') were grown in a soilless system under multiple agronomic conditions (electrical conductivity, substrate type, and coverage). Targeted metabolomic analysis of polyphenolic compounds, combined with advanced chemometric methods based on learning machines, revealed significant differences in multiple bioactives, such as chlorogenic acid, ellagic acid rhamnoside, sanguiin H10, quercetin 3-O-glucuronide, catechin, procyanidin B2, pelargonidin 3-O-glucoside, cyanidin 3-O-glucoside, and pelargonidin 3-O-rutinoside, which play a pivotal role in organoleptic properties and beneficial healthy effects of these polyphenol-rich foods.

  19. MASS SPECTROMETRY-BASED METABOLOMICS

    PubMed Central

    Dettmer, Katja; Aronov, Pavel A.; Hammock, Bruce D.

    2007-01-01

    This review presents an overview of the dynamically developing field of mass spectrometry-based metabolomics. Metabolomics aims at the comprehensive and quantitative analysis of wide arrays of metabolites in biological samples. These numerous analytes have very diverse physico-chemical properties and occur at different abundance levels. Consequently, comprehensive metabolomics investigations are primarily a challenge for analytical chemistry and specifically mass spectrometry has vast potential as a tool for this type of investigation. Metabolomics require special approaches for sample preparation, separation, and mass spectrometric analysis. Current examples of those approaches are described in this review. It primarily focuses on metabolic fingerprinting, a technique that analyzes all detectable analytes in a given sample with subsequent classification of samples and identification of differentially expressed metabolites, which define the sample classes. To perform this complex task, data analysis tools, metabolite libraries, and databases are required. Therefore, recent advances in metabolomics bioinformatics are also discussed. PMID:16921475

  20. Recommendations for Improving Identification and Quantification in Non-Targeted, GC-MS-Based Metabolomic Profiling of Human Plasma

    PubMed Central

    Wang, Hanghang; Muehlbauer, Michael J.; O’Neal, Sara K.; Newgard, Christopher B.; Hauser, Elizabeth R.; Shah, Svati H.

    2017-01-01

    The field of metabolomics as applied to human disease and health is rapidly expanding. In recent efforts of metabolomics research, greater emphasis has been placed on quality control and method validation. In this study, we report an experience with quality control and a practical application of method validation. Specifically, we sought to identify and modify steps in gas chromatography-mass spectrometry (GC-MS)-based, non-targeted metabolomic profiling of human plasma that could influence metabolite identification and quantification. Our experimental design included two studies: (1) a limiting-dilution study, which investigated the effects of dilution on analyte identification and quantification; and (2) a concentration-specific study, which compared the optimal plasma extract volume established in the first study with the volume used in the current institutional protocol. We confirmed that contaminants, concentration, repeatability and intermediate precision are major factors influencing metabolite identification and quantification. In addition, we established methods for improved metabolite identification and quantification, which were summarized to provide recommendations for experimental design of GC-MS-based non-targeted profiling of human plasma. PMID:28841195

  1. Stereoselective effects of ibuprofen in adult zebrafish (Danio rerio) using UPLC-TOF/MS-based metabolomics.

    PubMed

    Song, Yue; Chai, Tingting; Yin, Zhiqiang; Zhang, Xining; Zhang, Wei; Qian, Yongzhong; Qiu, Jing

    2018-06-09

    Ibuprofen (IBU), as a commonly used non-steroidal anti-inflammatory drug (NSAID) and pharmaceutical and personal care product (PPCP), is frequently prescribed by doctors to relieve pain. It is widely released into environmental water and soil in the form of chiral enantiomers by the urination and defecation of humans or animals and by sewage discharge from wastewater treatment plants. This study focused on the alteration of metabolism in the adult zebrafish (Danio rerio) brain after exposure to R-(-)-/S-(+)-/rac-IBU at 5 μg L -1 for 28 days. A total of 45 potential biomarkers and related pathways, including amino acids and their derivatives, purine and its derivatives, nucleotides and other metabolites, were observed with untargeted metabolomics. To validate the metabolic disorders induced by IBU, 22 amino acids and 3 antioxidant enzymes were selected to be quantitated and determined using targeted metabolomics and enzyme assay. Stereoselective changes were observed in the 45 identified biomarkers from the untargeted metabolomics analysis. The 22 amino acids quantitated in targeted metabolomics and 3 antioxidant enzymes determined in enzyme assay also showed stereoselective changes after R-(-)-/S-(+)-/rac-IBU exposure. Results showed that even at a low concentration of R-(-)-/S-(+)-/rac-IBU, disorders in metabolism and antioxidant defense systems were still induced with stereoselectivity. Our study may enable a better understanding of the risks of chiral PPCPs in aquatic organisms in the environment. Copyright © 2018 Elsevier Ltd. All rights reserved.

  2. Quantitative Serum Nuclear Magnetic Resonance Metabolomics in Large-Scale Epidemiology: A Primer on -Omic Technologies

    PubMed Central

    Kangas, Antti J; Soininen, Pasi; Lawlor, Debbie A; Davey Smith, George; Ala-Korpela, Mika

    2017-01-01

    Abstract Detailed metabolic profiling in large-scale epidemiologic studies has uncovered novel biomarkers for cardiometabolic diseases and clarified the molecular associations of established risk factors. A quantitative metabolomics platform based on nuclear magnetic resonance spectroscopy has found widespread use, already profiling over 400,000 blood samples. Over 200 metabolic measures are quantified per sample; in addition to many biomarkers routinely used in epidemiology, the method simultaneously provides fine-grained lipoprotein subclass profiling and quantification of circulating fatty acids, amino acids, gluconeogenesis-related metabolites, and many other molecules from multiple metabolic pathways. Here we focus on applications of magnetic resonance metabolomics for quantifying circulating biomarkers in large-scale epidemiology. We highlight the molecular characterization of risk factors, use of Mendelian randomization, and the key issues of study design and analyses of metabolic profiling for epidemiology. We also detail how integration of metabolic profiling data with genetics can enhance drug development. We discuss why quantitative metabolic profiling is becoming widespread in epidemiology and biobanking. Although large-scale applications of metabolic profiling are still novel, it seems likely that comprehensive biomarker data will contribute to etiologic understanding of various diseases and abilities to predict disease risks, with the potential to translate into multiple clinical settings. PMID:29106475

  3. Impact of a western diet on the ovarian and serum metabolome.

    PubMed

    Dhungana, Suraj; Carlson, James E; Pathmasiri, Wimal; McRitchie, Susan; Davis, Matt; Sumner, Susan; Appt, Susan E

    2016-10-01

    The objective of this investigation was to determine differences in the profiles of endogenous metabolites (metabolomics) among ovaries and serum derived from Old World nonhuman primates fed prudent or Western diets. A retrospective, observational study was done using archived ovarian tissue and serum from midlife cynomolgus monkeys (Macaca fasicularis). Targeted and broad spectrum metabolomics analysis was used to compare ovarian tissue and serum from monkeys that had been exposed to a prudent diet or a Western diet. Monkeys in the prudent diet group (n=13) were research naïve and had been exposed only to a commercial monkey chow diet (low in cholesterol and saturated fats, high in complex carbohydrates). Western diet monkeys (n=8) had consumed a diet that was high in cholesterol, saturated animal fats and soluble carbohydrates for 2 years prior to ovarian tissue and serum collection. Metabolomic analyses were done on extracts of homogenized ovary tissue samples, and extracts of serum. Targeted analysis was conducted using the Biocrates p180 kit and broad spectrum analysis was conducted using UPLC-TOF-MS, resulting in the detection of 3500 compound ions. Using metabolomics methods, which capture thousands of signals for metabolites, 64 metabolites were identified in serum and 47 metabolites were identified in ovarian tissue that differed by diet. Quantitative targeted analysis revealed 13 amino acids, 6 acrylcarnitines, and 2 biogenic amines that were significantly (p<0.05) different between the two diet groups for serum extracts, and similar results were observed for the ovary extracts. These data demonstrate that dietary exposure had a significant impact on the serum and ovarian metabolome, and demonstrated perturbation in carnitine, lipids/fatty acid, and amino acid metabolic pathways. Published by Elsevier Ireland Ltd.

  4. Metabolomic approach for improving ethanol stress tolerance in Saccharomyces cerevisiae.

    PubMed

    Ohta, Erika; Nakayama, Yasumune; Mukai, Yukio; Bamba, Takeshi; Fukusaki, Eiichiro

    2016-04-01

    The budding yeast Saccharomyces cerevisiae is widely used for brewing and ethanol production. The ethanol sensitivity of yeast cells is still a serious problem during ethanol fermentation, and a variety of genetic approaches (e.g., random mutant screening under selective pressure of ethanol) have been developed to improve ethanol tolerance. In this study, we developed a strategy for improving ethanol tolerance of yeast cells based on metabolomics as a high-resolution quantitative phenotypic analysis. We performed gas chromatography-mass spectrometry analysis to identify and quantify 36 compounds on 14 mutant strains including knockout strains for transcription factor and metabolic enzyme genes. A strong relation between metabolome of these mutants and their ethanol tolerance was observed. Data mining of the metabolomic analysis showed that several compounds (such as trehalose, valine, inositol and proline) contributed highly to ethanol tolerance. Our approach successfully detected well-known ethanol stress related metabolites such as trehalose and proline thus, to further prove our strategy, we focused on valine and inositol as the most promising target metabolites in our study. Our results show that simultaneous deletion of LEU4 and LEU9 (leading to accumulation of valine) or INM1 and INM2 (leading to reduction of inositol) significantly enhanced ethanol tolerance. This study shows the potential of the metabolomic approach to identify target genes for strain improvement of S. cerevisiae with higher ethanol tolerance. Copyright © 2015 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  5. Metabolomic applications in radiation biodosimetry: exploring radiation effects through small molecules.

    PubMed

    Pannkuk, Evan L; Fornace, Albert J; Laiakis, Evagelia C

    2017-10-01

    Exposure of the general population to ionizing radiation has increased in the past decades, primarily due to long distance travel and medical procedures. On the other hand, accidental exposures, nuclear accidents, and elevated threats of terrorism with the potential detonation of a radiological dispersal device or improvised nuclear device in a major city, all have led to increased needs for rapid biodosimetry and assessment of exposure to different radiation qualities and scenarios. Metabolomics, the qualitative and quantitative assessment of small molecules in a given biological specimen, has emerged as a promising technology to allow for rapid determination of an individual's exposure level and metabolic phenotype. Advancements in mass spectrometry techniques have led to untargeted (discovery phase, global assessment) and targeted (quantitative phase) methods not only to identify biomarkers of radiation exposure, but also to assess general perturbations of metabolism with potential long-term consequences, such as cancer, cardiovascular, and pulmonary disease. Metabolomics of radiation exposure has provided a highly informative snapshot of metabolic dysregulation. Biomarkers in easily accessible biofluids and biospecimens (urine, blood, saliva, sebum, fecal material) from mouse, rat, and minipig models, to non-human primates and humans have provided the basis for determination of a radiation signature to assess the need for medical intervention. Here we provide a comprehensive description of the current status of radiation metabolomic studies for the purpose of rapid high-throughput radiation biodosimetry in easily accessible biofluids and discuss future directions of radiation metabolomics research.

  6. Metabolomics in Toxicology and Preclinical Research

    PubMed Central

    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

  7. Applied metabolomics in drug discovery.

    PubMed

    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.

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

    PubMed

    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.

  9. Differentiating signals to make biological sense - A guide through databases for MS-based non-targeted metabolomics.

    PubMed

    Gil de la Fuente, Alberto; Grace Armitage, Emily; Otero, Abraham; Barbas, Coral; Godzien, Joanna

    2017-09-01

    Metabolite identification is one of the most challenging steps in metabolomics studies and reflects one of the greatest bottlenecks in the entire workflow. The success of this step determines the success of the entire research, therefore the quality at which annotations are given requires special attention. A variety of tools and resources are available to aid metabolite identification or annotation, offering different and often complementary functionalities. In preparation for this article, almost 50 databases were reviewed, from which 17 were selected for discussion, chosen for their online ESI-MS functionality. The general characteristics and functions of each database is discussed in turn, considering the advantages and limitations of each along with recommendations for optimal use of each tool, as derived from experiences encountered at the Centre for Metabolomics and Bioanalysis (CEMBIO) in Madrid. These databases were evaluated considering their utility in non-targeted metabolomics, including aspects such as identifier assignment, structural assignment and interpretation of results. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Binary similarity measures for fingerprint analysis of qualitative metabolomic profiles.

    PubMed

    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.

  11. 12-months metabolic changes among gender dysphoric individuals under cross-sex hormone treatment: a targeted metabolomics study

    PubMed Central

    Auer, Matthias K.; Cecil, Alexander; Roepke, Yasmin; Bultynck, Charlotte; Pas, Charlotte; Fuss, Johannes; Prehn, Cornelia; Wang-Sattler, Rui; Adamski, Jerzy; Stalla, Günter K.; T’Sjoen, Guy

    2016-01-01

    Metabolomic analyses in epidemiological studies have demonstrated a strong sexual dimorphism for most metabolites. Cross-sex hormone treatment (CSH) in transgender individuals enables the study of metabolites in a cross-gender setting. Targeted metabolomic profiling of serum of fasting transmen and transwomen at baseline and following 12 months of CSH (N = 20/group) was performed. Changes in 186 serum metabolites and metabolite ratios were determined by targeted metabolomics analysis based on ESI-LC-MS/MS. RandomForest (RF) analysis was applied to detect metabolites of highest interest for grouping of transwomen and transmen before and after initiation of CSH. Principal component analysis (PCA) was performed to check whether group differentiation was achievable according to these variables and to see if changes in metabolite levels could be explained by a priori gender differences. PCA predicted grouping of individuals-determined by the citrulline/arginine-ratio and the amino acids lysine, alanine and asymmetric dimethylarginine - in addition to the expected grouping due to changes in sex steroids and body composition. The fact that most of the investigated metabolites did, however, not change, indicates that the majority of sex dependent differences in metabolites reported in the literature before may primarily not be attributable to sex hormones but to other gender-differences. PMID:27833161

  12. Metabolomics in Newborns.

    PubMed

    Noto, Antonio; Fanos, Vassilios; Dessì, Angelica

    2016-01-01

    Metabolomics is the quantitative analysis of a large number of low molecular weight metabolites that are intermediate or final products of all the metabolic pathways in a living organism. Any metabolic profiles detectable in a human biological fluid are caused by the interaction between gene expression and the environment. The metabolomics approach offers the possibility to identify variations in metabolite profile that can be used to discriminate disease. This is particularly important for neonatal and pediatric studies especially for severe ill patient diagnosis and early identification. This property is of a great clinical importance in view of the newer definitions of health and disease. This review emphasizes the workflow of a typical metabolomics study and summarizes the latest results obtained in neonatal studies with particular interest in prematurity, intrauterine growth retardation, inborn errors of metabolism, perinatal asphyxia, sepsis, necrotizing enterocolitis, kidney disease, bronchopulmonary dysplasia, and cardiac malformation and dysfunction. © 2016 Elsevier Inc. All rights reserved.

  13. Neuronal metabolomics by ion mobility mass spectrometry: cocaine effects on glucose and selected biogenic amine metabolites in the frontal cortex, striatum, and thalamus of the rat.

    PubMed

    Kaplan, Kimberly A; Chiu, Veronica M; Lukus, Peter A; Zhang, Xing; Siems, William F; Schenk, James O; Hill, Herbert H

    2013-02-01

    We report results of studies of global and targeted neuronal metabolomes by ambient pressure ion mobility mass spectrometry. The rat frontal cortex, striatum, and thalamus were sampled from control nontreated rats and those treated with acute cocaine or pargyline. Quantitative evaluations were made by standard additions or isotopic dilution. The mass detection limit was ~100 pmol varying with the analyte. Targeted metabolites of dopamine, serotonin, and glucose followed the rank order of distribution expected between the anatomical areas. Data was evaluated by principal component analysis on 764 common metabolites (identified by m/z and reduced mobility). Differences between anatomical areas and treatment groups were observed for 53 % of these metabolites using principal component analysis. Global and targeted metabolic differences were observed between the three anatomical areas with contralateral differences between some areas. Following drug treatments, global and targeted metabolomes were found to shift relative to controls and still maintained anatomical differences. Pargyline reduced 3,4-dihydroxyphenylacetic acid below detection limits, and 5-HIAA varied between anatomical regions. Notable findings were: (1) global metabolomes were different between anatomical areas and were altered by acute cocaine providing a broad but targeted window of discovery for metabolic changes produced by drugs of abuse; (2) quantitative analysis was demonstrated using isotope dilution and standard addition; (3) cocaine changed glucose and biogenic amine metabolism in the anatomical areas tested; and (4) the largest effect of cocaine was on the glycolysis metabolome in the thalamus confirming inferences from previous positron emission tomography studies using 2-deoxyglucose.

  14. Systematic Applications of Metabolomics in Metabolic Engineering

    PubMed Central

    Dromms, Robert A.; Styczynski, Mark P.

    2012-01-01

    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. PMID:24957776

  15. Putative regulatory sites unraveled by network-embedded thermodynamic analysis of metabolome data

    PubMed Central

    Kümmel, Anne; Panke, Sven; Heinemann, Matthias

    2006-01-01

    As one of the most recent members of the omics family, large-scale quantitative metabolomics data are currently complementing our systems biology data pool and offer the chance to integrate the metabolite level into the functional analysis of cellular networks. Network-embedded thermodynamic analysis (NET analysis) is presented as a framework for mechanistic and model-based analysis of these data. By coupling the data to an operating metabolic network via the second law of thermodynamics and the metabolites' Gibbs energies of formation, NET analysis allows inferring functional principles from quantitative metabolite data; for example it identifies reactions that are subject to active allosteric or genetic regulation as exemplified with quantitative metabolite data from Escherichia coli and Saccharomyces cerevisiae. Moreover, the optimization framework of NET analysis was demonstrated to be a valuable tool to systematically investigate data sets for consistency, for the extension of sub-omic metabolome data sets and for resolving intracompartmental concentrations from cell-averaged metabolome data. Without requiring any kind of kinetic modeling, NET analysis represents a perfectly scalable and unbiased approach to uncover insights from quantitative metabolome data. PMID:16788595

  16. Can NMR solve some significant challenges in metabolomics?

    PubMed Central

    Gowda, G.A. Nagana; Raftery, Daniel

    2015-01-01

    The field of metabolomics continues to witness rapid growth driven by fundamental studies, methods development, and applications in a number of disciplines that include biomedical science, plant and nutrition sciences, drug development, energy and environmental sciences, toxicology, etc. NMR spectroscopy is one of the two most widely used analytical platforms in the metabolomics field, along with mass spectrometry (MS). NMR's excellent reproducibility and quantitative accuracy, its ability to identify structures of unknown metabolites, its capacity to generate metabolite profiles using intact biospecimens with no need for separation, and its capabilities for tracing metabolic pathways using isotope labeled substrates offer unique strengths for metabolomics applications. However, NMR's limited sensitivity and resolution continue to pose a major challenge and have restricted both the number and the quantitative accuracy of metabolites analyzed by NMR. Further, the analysis of highly complex biological samples has increased the demand for new methods with improved detection, better unknown identification, and more accurate quantitation of larger numbers of metabolites. Recent efforts have contributed significant improvements in these areas, and have thereby enhanced the pool of routinely quantifiable metabolites. Additionally, efforts focused on combining NMR and MS promise opportunities to exploit the combined strength of the two analytical platforms for direct comparison of the metabolite data, unknown identification and reliable biomarker discovery that continue to challenge the metabolomics field. This article presents our perspectives on the emerging trends in NMR-based metabolomics and NMR's continuing role in the field with an emphasis on recent and ongoing research from our laboratory. PMID:26476597

  17. Can NMR solve some significant challenges in metabolomics?

    PubMed

    Nagana Gowda, G A; Raftery, Daniel

    2015-11-01

    The field of metabolomics continues to witness rapid growth driven by fundamental studies, methods development, and applications in a number of disciplines that include biomedical science, plant and nutrition sciences, drug development, energy and environmental sciences, toxicology, etc. NMR spectroscopy is one of the two most widely used analytical platforms in the metabolomics field, along with mass spectrometry (MS). NMR's excellent reproducibility and quantitative accuracy, its ability to identify structures of unknown metabolites, its capacity to generate metabolite profiles using intact bio-specimens with no need for separation, and its capabilities for tracing metabolic pathways using isotope labeled substrates offer unique strengths for metabolomics applications. However, NMR's limited sensitivity and resolution continue to pose a major challenge and have restricted both the number and the quantitative accuracy of metabolites analyzed by NMR. Further, the analysis of highly complex biological samples has increased the demand for new methods with improved detection, better unknown identification, and more accurate quantitation of larger numbers of metabolites. Recent efforts have contributed significant improvements in these areas, and have thereby enhanced the pool of routinely quantifiable metabolites. Additionally, efforts focused on combining NMR and MS promise opportunities to exploit the combined strength of the two analytical platforms for direct comparison of the metabolite data, unknown identification and reliable biomarker discovery that continue to challenge the metabolomics field. This article presents our perspectives on the emerging trends in NMR-based metabolomics and NMR's continuing role in the field with an emphasis on recent and ongoing research from our laboratory. Copyright © 2015 Elsevier Inc. All rights reserved.

  18. Can NMR solve some significant challenges in metabolomics?

    NASA Astrophysics Data System (ADS)

    Nagana Gowda, G. A.; Raftery, Daniel

    2015-11-01

    The field of metabolomics continues to witness rapid growth driven by fundamental studies, methods development, and applications in a number of disciplines that include biomedical science, plant and nutrition sciences, drug development, energy and environmental sciences, toxicology, etc. NMR spectroscopy is one of the two most widely used analytical platforms in the metabolomics field, along with mass spectrometry (MS). NMR's excellent reproducibility and quantitative accuracy, its ability to identify structures of unknown metabolites, its capacity to generate metabolite profiles using intact bio-specimens with no need for separation, and its capabilities for tracing metabolic pathways using isotope labeled substrates offer unique strengths for metabolomics applications. However, NMR's limited sensitivity and resolution continue to pose a major challenge and have restricted both the number and the quantitative accuracy of metabolites analyzed by NMR. Further, the analysis of highly complex biological samples has increased the demand for new methods with improved detection, better unknown identification, and more accurate quantitation of larger numbers of metabolites. Recent efforts have contributed significant improvements in these areas, and have thereby enhanced the pool of routinely quantifiable metabolites. Additionally, efforts focused on combining NMR and MS promise opportunities to exploit the combined strength of the two analytical platforms for direct comparison of the metabolite data, unknown identification and reliable biomarker discovery that continue to challenge the metabolomics field. This article presents our perspectives on the emerging trends in NMR-based metabolomics and NMR's continuing role in the field with an emphasis on recent and ongoing research from our laboratory.

  19. Introduction to metabolomics and its applications in ophthalmology

    PubMed Central

    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

  20. Influential Parameters for the Analysis of Intracellular Parasite Metabolomics.

    PubMed

    Carey, Maureen A; Covelli, Vincent; Brown, Audrey; Medlock, Gregory L; Haaren, Mareike; Cooper, Jessica G; Papin, Jason A; Guler, Jennifer L

    2018-04-25

    Metabolomics is increasingly popular for the study of pathogens. For the malaria parasite Plasmodium falciparum , both targeted and untargeted metabolomics have improved our understanding of pathogenesis, host-parasite interactions, and antimalarial drug treatment and resistance. However, purification and analysis procedures for performing metabolomics on intracellular pathogens have not been explored. Here, we purified in vitro -grown ring-stage intraerythrocytic P. falciparum parasites for untargeted metabolomics studies; the small size of this developmental stage amplifies the challenges associated with metabolomics studies as the ratio between host and parasite biomass is maximized. Following metabolite identification and data preprocessing, we explored multiple confounding factors that influence data interpretation, including host contamination and normalization approaches (including double-stranded DNA, total protein, and parasite numbers). We conclude that normalization parameters have large effects on differential abundance analysis and recommend the thoughtful selection of these parameters. However, normalization does not remove the contribution from the parasite's extracellular environment (culture media and host erythrocyte). In fact, we found that extraparasite material is as influential on the metabolome as treatment with a potent antimalarial drug with known metabolic effects (artemisinin). Because of this influence, we could not detect significant changes associated with drug treatment. Instead, we identified metabolites predictive of host and medium contamination that could be used to assess sample purification. Our analysis provides the first quantitative exploration of the effects of these factors on metabolomics data analysis; these findings provide a basis for development of improved experimental and analytical methods for future metabolomics studies of intracellular organisms. IMPORTANCE Molecular characterization of pathogens such as the

  1. The Human Urine Metabolome

    PubMed Central

    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

  2. METABOLOMICS IN SMALL FISH TOXICOLOGY AND OTHER ENVIRONMENTAL APPLICATIONS

    EPA Science Inventory

    Although lagging behind applications targeted to human endpoints, metabolomics offers great potential in environmental applications, including ecotoxicology. Indeed, the advantages of metabolomics (relative to other 'omic techniques) may be more tangible in ecotoxicology because...

  3. Use of NMR Metabolomics to Analyze the Targets of D-cycloserine in Mycobacteria: Role of D-Alanine Racemase

    PubMed Central

    Halouska, Steven; Chacon, Ofelia; Fenton, Robert J.; Zinniel, Denise K.; Barletta, Raul G.; Powers, Robert

    2008-01-01

    D-cycloserine (DCS) is only used with multi-drug resistant strains of tuberculosis because of serious side-effects. DCS is known to inhibit cell wall biosynthesis, but the in vivo lethal target is still unknown. We have applied NMR-based metabolomics combined with principal component analysis to monitor the in vivo affect of DCS on M. smegmatis. Our analysis suggests DCS functions by inhibiting multiple protein targets. PMID:17979227

  4. Untargeted Metabolomics Strategies—Challenges and Emerging Directions

    NASA Astrophysics Data System (ADS)

    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.

  5. Quantitative Systems Pharmacology Model of NO Metabolome and Methemoglobin Following Long-Term Infusion of Sodium Nitrite in Humans

    PubMed Central

    Vega-Villa, K; Pluta, R; Lonser, R; Woo, S

    2013-01-01

    A long-term sodium nitrite infusion is intended for the treatment of vascular disorders. Phase I data demonstrated a significant nonlinear dose-exposure-toxicity relationship within the therapeutic dosage range. This study aims to develop a quantitative systems pharmacology model characterizing nitric oxide (NO) metabolome and methemoglobin after sodium nitrite infusion. Nitrite, nitrate, and methemoglobin concentration–time profiles in plasma and RBC were used for model development. Following intravenous sodium nitrite administration, nitrite undergoes conversion in RBC and tissue. Nitrite sequestered by RBC interacts more extensively with deoxyhemoglobin, which contributes greatly to methemoglobin formation. Methemoglobin is formed less-than-proportionally at higher nitrite doses as characterized with facilitated methemoglobin removal. Nitrate-to-nitrite reduction occurs in tissue and via entero-salivary recirculation. The less-than-proportional increase in nitrite and nitrate exposure at higher nitrite doses is modeled with a dose-dependent increase in clearance. The model provides direct insight into NO metabolome disposition and is valuable for nitrite dosing selection in clinical trials. PMID:23903463

  6. Large-Scale Metabolomics Reveals A Complex Response of Aspergillus nidulans to Epigenetic Perturbation

    PubMed Central

    Albright, Jessica C.; Henke, Matthew T.; Soukup, Alexandra A.; McClure, Ryan A.; Thomson, Regan J.; Keller, Nancy P.; Kelleher, Neil L.

    2015-01-01

    The microbial world offers a rich source of bioactive compounds for those able to sift through it. Technologies capable of quantitatively detecting natural products while simultaneously identifying known compounds would expedite the search for new pharmaceutical leads. Prior efforts have targeted histone deacetylases in fungi to globally activate the production of new secondary metabolites, yet no study has directly assessed its effects with minimal bias at the metabolomic level. Using untargeted metabolomics, we monitored changes in >1000 small molecules secreted from the model fungus, Aspergillus nidulans, following genetic or chemical reductions in histone deacetylase activity (HDACi). Through quantitative, differential analyses, we found nearly equal numbers of compounds were up- and down-regulated by >100 fold. We detected products from both known and unknown biosynthetic pathways and discovered that A. nidulans is capable of producing fellutamides, proteasome inhibitors whose expression was induced by ~100 fold or greater upon HDACi. This work adds momentum to an ‘omics’-driven resurgence in natural products research, where direct detection replaces bioactivity as the primary screen for new pharmacophores. PMID:25815712

  7. Comparison of Metabolomics Approaches for Evaluating the Variability of Complex Botanical Preparations: Green Tea (Camellia sinensis) as a Case Study.

    PubMed

    Kellogg, Joshua J; Graf, Tyler N; Paine, Mary F; McCune, Jeannine S; Kvalheim, Olav M; Oberlies, Nicholas H; Cech, Nadja B

    2017-05-26

    A challenge that must be addressed when conducting studies with complex natural products is how to evaluate their complexity and variability. Traditional methods of quantifying a single or a small range of metabolites may not capture the full chemical complexity of multiple samples. Different metabolomics approaches were evaluated to discern how they facilitated comparison of the chemical composition of commercial green tea [Camellia sinensis (L.) Kuntze] products, with the goal of capturing the variability of commercially used products and selecting representative products for in vitro or clinical evaluation. Three metabolomic-related methods-untargeted ultraperformance liquid chromatography-mass spectrometry (UPLC-MS), targeted UPLC-MS, and untargeted, quantitative 1 HNMR-were employed to characterize 34 commercially available green tea samples. Of these methods, untargeted UPLC-MS was most effective at discriminating between green tea, green tea supplement, and non-green-tea products. A method using reproduced correlation coefficients calculated from principal component analysis models was developed to quantitatively compare differences among samples. The obtained results demonstrated the utility of metabolomics employing UPLC-MS data for evaluating similarities and differences between complex botanical products.

  8. Comparison of Metabolomics Approaches for Evaluating the Variability of Complex Botanical Preparations: Green Tea (Camellia sinensis) as a Case Study

    PubMed Central

    2017-01-01

    A challenge that must be addressed when conducting studies with complex natural products is how to evaluate their complexity and variability. Traditional methods of quantifying a single or a small range of metabolites may not capture the full chemical complexity of multiple samples. Different metabolomics approaches were evaluated to discern how they facilitated comparison of the chemical composition of commercial green tea [Camellia sinensis (L.) Kuntze] products, with the goal of capturing the variability of commercially used products and selecting representative products for in vitro or clinical evaluation. Three metabolomic-related methods—untargeted ultraperformance liquid chromatography–mass spectrometry (UPLC-MS), targeted UPLC-MS, and untargeted, quantitative 1HNMR—were employed to characterize 34 commercially available green tea samples. Of these methods, untargeted UPLC-MS was most effective at discriminating between green tea, green tea supplement, and non-green-tea products. A method using reproduced correlation coefficients calculated from principal component analysis models was developed to quantitatively compare differences among samples. The obtained results demonstrated the utility of metabolomics employing UPLC-MS data for evaluating similarities and differences between complex botanical products. PMID:28453261

  9. Enzyme-driven metabolomic screening: a proof-of-principle method for discovery of plant defence compounds targeted by pathogens.

    PubMed

    Carere, Jason; Colgrave, Michelle L; Stiller, Jiri; Liu, Chunji; Manners, John M; Kazan, Kemal; Gardiner, Donald M

    2016-11-01

    Plants produce a variety of secondary metabolites to defend themselves from pathogen attack, while pathogens have evolved to overcome plant defences by producing enzymes that degrade or modify these defence compounds. However, many compounds targeted by pathogen enzymes currently remain enigmatic. Identifying host compounds targeted by pathogen enzymes would enable us to understand the potential importance of such compounds in plant defence and modify them to make them insensitive to pathogen enzymes. Here, a proof of concept metabolomics-based method was developed to discover plant defence compounds modified by pathogens using two pathogen enzymes with known targets in wheat and tomato. Plant extracts treated with purified pathogen enzymes were subjected to LC-MS, and the relative abundance of metabolites before and after treatment were comparatively analysed. Using two enzymes from different pathogens the in planta targets could be found by combining relatively simple enzymology with the power of untargeted metabolomics. Key to the method is dataset simplification based on natural isotope occurrence and statistical filtering, which can be scripted. The method presented here will aid in our understanding of plant-pathogen interactions and may lead to the development of new plant protection strategies. © 2016 CSIRO. New Phytologist © 2016 New Phytologist Trust.

  10. Understanding Environmental Tobacco Smoke Exposure and Effects in Asthmatic Children through Determination of Urinary Cotinine and Targeted Metabolomics of Plasma

    EPA Science Inventory

    Understanding Environmental Tobacco Smoke Exposure and Effects in Asthmatic Children through Determination of Urinary Cotinine and Targeted Metabolomics of Plasma Introduction Asthma is a complex disease with multiple triggers and causal factors, Exposure to environmental tob...

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

    PubMed

    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

  12. Time is ripe: maturation of metabolomics in chronobiology.

    PubMed

    Rhoades, Seth D; Sengupta, Arjun; Weljie, Aalim M

    2017-02-01

    Sleep and circadian rhythms studies have recently benefited from metabolomics analyses, uncovering new connections between chronobiology and metabolism. From untargeted mass spectrometry to quantitative nuclear magnetic resonance spectroscopy, a diversity of analytical approaches has been applied for biomarker discovery in the field. In this review we consider advances in the application of metabolomics technologies which have uncovered significant effects of sleep and circadian cycles on several metabolites, namely phosphatidylcholine species, medium-chain carnitines, and aromatic amino acids. Study design and data processing measures essential for detecting rhythmicity in metabolomics data are also discussed. Future developments in these technologies are anticipated vis-à-vis validating early findings, given metabolomics has only recently entered the ring with other systems biology assessments in chronometabolism studies. Copyright © 2016 Elsevier Ltd. All rights reserved.

  13. Retinal metabolic events in preconditioning light stress as revealed by wide-spectrum targeted metabolomics.

    PubMed

    de la Barca, Juan Manuel Chao; Huang, Nuan-Ting; Jiao, Haihan; Tessier, Lydie; Gadras, Cédric; Simard, Gilles; Natoli, Riccardo; Tcherkez, Guillaume; Reynier, Pascal; Valter, Krisztina

    2017-01-01

    Light is the primary stimulus for vision, but may also cause damage to the retina. Pre-exposing the retina to sub-lethal amount of light (or preconditioning) improves chances for retinal cells to survive acute damaging light stress. This study aims at exploring the changes in retinal metabolome after mild light stress and identifying mechanisms that may be involved in preconditioning. Retinas from 12 rats exposed to mild light stress (1000 lux × for 12 h) and 12 controls were collected one and seven days after light stress (LS). One retina was used for targeted metabolomics analysis using the Biocrates p180 kit while the fellow retina was used for histological and immunohistochemistry analysis. Immunohistochemistry confirmed that in this experiment, a mild LS with retinal immune response and minimal photoreceptor loss occurred. Compared to controls, LS induced an increased concentration in phosphatidylcholines. The concentration in some amino acids and biogenic amines, particularly those related to the nitric oxide pathway (like asymmetric dimethylarginine (ADMA), arginine and citrulline) also increased 1 day after LS. 7 days after LS, the concentration in two sphingomyelins and phenylethylamine was found to be higher. We further found that in controls, retina metabolome was different between males and females: male retinas had an increased concentration in tyrosine, acetyl-ornithine, phosphatidylcholines and (acyl)-carnitines. Besides retinal sexual metabolic dimorphism, this study shows that preconditioning is mostly associated with re-organisation of lipid metabolism and changes in amino acid composition, likely reflecting the involvement of arginine-dependent NO signalling.

  14. NMR-based Metabolomics for Cancer Research

    EPA Science Inventory

    Metabolomics is considered as a complementary tool to other omics platforms to provide a snapshot of the cellular biochemistry and physiology taking place at any instant. Metabolmics approaches have been widely used to provide comprehensive and quantitative analyses of the metabo...

  15. Non-targeted metabolomic biomarkers and metabotypes of type 2 diabetes: A cross-sectional study of PREDIMED trial participants.

    PubMed

    Urpi-Sarda, M; Almanza-Aguilera, E; Llorach, R; Vázquez-Fresno, R; Estruch, R; Corella, D; Sorli, J V; Carmona, F; Sanchez-Pla, A; Salas-Salvadó, J; Andres-Lacueva, C

    2018-02-20

    To characterize the urinary metabolomic fingerprint and multi-metabolite signature associated with type 2 diabetes (T2D), and to classify the population into metabotypes related to T2D. A metabolomics analysis using the 1 H-NMR-based, non-targeted metabolomic approach was conducted to determine the urinary metabolomic fingerprint of T2D compared with non-T2D participants in the PREDIMED trial. The discriminant metabolite fingerprint was subjected to logistic regression analysis and ROC analyses to establish and to assess the multi-metabolite signature of T2D prevalence, respectively. Metabotypes associated with T2D were identified using the k-means algorithm. A total of 33 metabolites were significantly different (P<0.05) between T2D and non-T2D participants. The multi-metabolite signature of T2D comprised high levels of methylsuccinate, alanine, dimethylglycine and guanidoacetate, and reduced levels of glutamine, methylguanidine, 3-hydroxymandelate and hippurate, and had a 96.4% AUC, which was higher than the metabolites on their own and glucose. Amino-acid and carbohydrate metabolism were the main metabolic alterations in T2D, and various metabotypes were identified in the studied population. Among T2D participants, those with a metabotype of higher levels of phenylalanine, phenylacetylglutamine, p-cresol and acetoacetate had significantly higher levels of plasma glucose. The multi-metabolite signature of T2D highlights the altered metabolic fingerprint associated mainly with amino-acid, carbohydrate and microbiota metabolism. Metabotypes identified in this patient population could be related to higher risk of long-term cardiovascular events and therefore require further studies. Metabolomics is a useful tool for elucidating the metabolic complexity and interindividual variation in T2D towards the development of stratified precision nutrition and medicine. Trial registration at www.controlled-trials.com: ISRCTN35739639. Copyright © 2018 Elsevier Masson SAS. All

  16. Metabolomics and Diabetes: Analytical and Computational Approaches

    PubMed Central

    Sas, Kelli M.; Karnovsky, Alla; Michailidis, George

    2015-01-01

    Diabetes is characterized by altered metabolism of key molecules and regulatory pathways. The phenotypic expression of diabetes and associated complications encompasses complex interactions between genetic, environmental, and tissue-specific factors that require an integrated understanding of perturbations in the network of genes, proteins, and metabolites. Metabolomics attempts to systematically identify and quantitate small molecule metabolites from biological systems. The recent rapid development of a variety of analytical platforms based on mass spectrometry and nuclear magnetic resonance have enabled identification of complex metabolic phenotypes. Continued development of bioinformatics and analytical strategies has facilitated the discovery of causal links in understanding the pathophysiology of diabetes and its complications. Here, we summarize the metabolomics workflow, including analytical, statistical, and computational tools, highlight recent applications of metabolomics in diabetes research, and discuss the challenges in the field. PMID:25713200

  17. Metabolomics Guides Rational Development of a Simplified Cell Culture Medium for Drug Screening against Trypanosoma brucei

    PubMed Central

    Creek, Darren J.; Nijagal, Brunda; Kim, Dong-Hyun; Rojas, Federico; Matthews, Keith R.

    2013-01-01

    In vitro culture methods underpin many experimental approaches to biology and drug discovery. The modification of established cell culture methods to make them more biologically relevant or to optimize growth is traditionally a laborious task. Emerging metabolomic technology enables the rapid evaluation of intra- and extracellular metabolites and can be applied to the rational development of cell culture media. In this study, untargeted semiquantitative and targeted quantitative metabolomic analyses of fresh and spent media revealed the major nutritional requirements for the growth of bloodstream form Trypanosoma brucei. The standard culture medium (HMI11) contained unnecessarily high concentrations of 32 nutrients that were subsequently removed to make the concentrations more closely resemble those normally found in blood. Our new medium, Creek's minimal medium (CMM), supports in vitro growth equivalent to that in HMI11 and causes no significant perturbation of metabolite levels for 94% of the detected metabolome (<3-fold change; α = 0.05). Importantly, improved sensitivity was observed for drug activity studies in whole-cell phenotypic screenings and in the metabolomic mode of action assays. Four-hundred-fold 50% inhibitory concentration decreases were observed for pentamidine and methotrexate, suggesting inhibition of activity by nutrients present in HMI11. CMM is suitable for routine cell culture and offers important advantages for metabolomic studies and drug activity screening. PMID:23571546

  18. Causal Genetic Variation Underlying Metabolome Differences.

    PubMed

    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.

  19. Metabolomics in Small Fish Toxicology: Assessing the Impacts of Model EDCs

    EPA Science Inventory

    Although lagging behind applications targeted to human endpoints, metabolomics offers great potential in environmental applications, including ecotoxicology. Indeed, the advantages of metabolomics (relative to other ‘omic techniques) may be more tangible in ecotoxicology because...

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

    PubMed

    Carroll, Adam J; Badger, Murray R; Harvey Millar, A

    2010-07-14

    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. 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. 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 assess data quality and draw their own insights from published

  1. Global metabolomic profiling targeting childhood obesity in the Hispanic population.

    PubMed

    Butte, Nancy F; Liu, Yan; Zakeri, Issa F; Mohney, Robert P; Mehta, Nitesh; Voruganti, V Saroja; Göring, Harald; Cole, Shelley A; Comuzzie, Anthony G

    2015-08-01

    Metabolomics may unravel important biological pathways involved in the pathophysiology of childhood obesity. We aimed to 1) identify metabolites that differ significantly between nonobese and obese Hispanic children; 2) collapse metabolites into principal components (PCs) associated with obesity and metabolic risk, specifically hyperinsulinemia, hypertriglyceridemia, hyperleptinemia, and hyperuricemia; and 3) identify metabolites associated with energy expenditure and fat oxidation. This trial was a cross-sectional observational study of metabolomics by using gas chromatography-mass spectrometry and ultrahigh-performance liquid chromatography-tandem mass spectrometry analyses performed on fasting plasma samples from 353 nonobese and 450 obese Hispanic children. Branched-chained amino acids (BCAAs) (Leu, Ile, and Val) and their catabolites, propionylcarnitine and butyrylcarnitine, were significantly elevated in obese children. Strikingly lower lysolipids and dicarboxylated fatty acids were seen in obese children. Steroid derivatives were markedly higher in obese children as were markers of inflammation and oxidative stress. PC6 (BCAAs and aromatic AAs) and PC10 (asparagine, glycine, and serine) made the largest contributions to body mass index, and PC10 and PC12 (acylcarnitines) made the largest contributions to adiposity. Metabolic risk factors and total energy expenditure were associated with PC6, PC9 (AA and tricarboxylic acid cycle metabolites), and PC10. Fat oxidation was inversely related to PC8 (lysolipids) and positively related to PC16 (acylcarnitines). Global metabolomic profiling in nonobese and obese children replicates the increased BCAA and acylcarnitine catabolism and changes in nucleotides, lysolipids, and inflammation markers seen in obese adults; however, a strong signature of reduced fatty acid catabolism and increased steroid derivatives may be unique to obese children. Metabolic flexibility in fuel use observed in obese children may occur

  2. Can Untargeted Metabolomics Be Utilized in Drug Discovery/Development?

    PubMed

    Caldwell, Gary W; Leo, Gregory C

    2017-01-01

    Untargeted metabolomics is a promising approach for reducing the significant attrition rate for discovering and developing drugs in the pharmaceutical industry. This review aims to highlight the practical decision-making value of untargeted metabolomics for the advancement of drug candidates in drug discovery/development including potentially identifying and validating novel therapeutic targets, creating alternative screening paradigms, facilitating the selection of specific and translational metabolite biomarkers, identifying metabolite signatures for the drug efficacy mechanism of action, and understanding potential drug-induced toxicity. The review provides an overview of the pharmaceutical process workflow to discover and develop new small molecule drugs followed by the metabolomics process workflow that is involved in conducting metabolomics studies. The pros and cons of the major components of the pharmaceutical and metabolomics workflows are reviewed and discussed. Finally, selected untargeted metabolomics literature examples, from primarily 2010 to 2016, are used to illustrate why, how, and where untargeted metabolomics can be integrated into the drug discovery/preclinical drug development process. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  3. Metabolomics of Small Numbers of Cells: Metabolomic Profiling of 100, 1000, and 10000 Human Breast Cancer Cells.

    PubMed

    Luo, Xian; Li, Liang

    2017-11-07

    In cellular metabolomics, it is desirable to carry out metabolomic profiling using a small number of cells in order to save time and cost. In some applications (e.g., working with circulating tumor cells in blood), only a limited number of cells are available for analysis. In this report, we describe a method based on high-performance chemical isotope labeling (CIL) nanoflow liquid chromatography mass spectrometry (nanoLC-MS) for high-coverage metabolomic analysis of small numbers of cells (i.e., ≤10000 cells). As an example, 12 C-/ 13 C-dansyl labeling of the metabolites in lysates of 100, 1000, and 10000 MCF-7 breast cancer cells was carried out using a new labeling protocol tailored to handle small amounts of metabolites. Chemical-vapor-assisted ionization in a captivespray interface was optimized for improving metabolite ionization and increasing robustness of nanoLC-MS. Compared to microflow LC-MS, the nanoflow system provided much improved metabolite detectability with a significantly reduced sample amount required for analysis. Experimental duplicate analyses of biological triplicates resulted in the detection of 1620 ± 148, 2091 ± 89 and 2402 ± 80 (n = 6) peak pairs or metabolites in the amine/phenol submetabolome from the 12 C-/ 13 C-dansyl labeled lysates of 100, 1000, and 10000 cells, respectively. About 63-69% of these peak pairs could be either identified using dansyl labeled standard library or mass-matched to chemical structures in human metabolome databases. We envisage the routine applications of this method for high-coverage quantitative cellular metabolomics using a starting material of 10000 cells. Even for analyzing 100 or 1000 cells, although the metabolomic coverage is reduced from the maximal coverage, this method can still detect thousands of metabolites, allowing the analysis of a large fraction of the metabolome and focused analysis of the detectable metabolites.

  4. Effect of Insulin Resistance on Monounsaturated Fatty Acid Levels: A Multi-cohort Non-targeted Metabolomics and Mendelian Randomization Study

    PubMed Central

    Ganna, Andrea; Brandmaier, Stefan; Broeckling, Corey D.; Prenni, Jessica E.; Wang-Sattler, Rui; Peters, Annette; Strauch, Konstantin; Meitinger, Thomas; Giedraitis, Vilmantas; Ärnlöv, Johan; Berne, Christian; Gieger, Christian; Ripatti, Samuli; Lind, Lars; Sundström, Johan; Ingelsson, Erik

    2016-01-01

    Insulin resistance (IR) and impaired insulin secretion contribute to type 2 diabetes and cardiovascular disease. Both are associated with changes in the circulating metabolome, but causal directions have been difficult to disentangle. We combined untargeted plasma metabolomics by liquid chromatography/mass spectrometry in three non-diabetic cohorts with Mendelian Randomization (MR) analysis to obtain new insights into early metabolic alterations in IR and impaired insulin secretion. In up to 910 elderly men we found associations of 52 metabolites with hyperinsulinemic-euglycemic clamp-measured IR and/or β-cell responsiveness (disposition index) during an oral glucose tolerance test. These implicated bile acid, glycerophospholipid and caffeine metabolism for IR and fatty acid biosynthesis for impaired insulin secretion. In MR analysis in two separate cohorts (n = 2,613) followed by replication in three independent studies profiled on different metabolomics platforms (n = 7,824 / 8,961 / 8,330), we discovered and replicated causal effects of IR on lower levels of palmitoleic acid and oleic acid. A trend for a causal effect of IR on higher levels of tyrosine reached significance only in meta-analysis. In one of the largest studies combining “gold standard” measures for insulin responsiveness with non-targeted metabolomics, we found distinct metabolic profiles related to IR or impaired insulin secretion. We speculate that the causal effects on monounsaturated fatty acid levels could explain parts of the raised cardiovascular disease risk in IR that is independent of diabetes development. PMID:27768686

  5. High Resolution Separations and Improved Ion Production and Transmission in Metabolomics

    PubMed Central

    Metz, Thomas O.; Page, Jason S.; Baker, Erin S.; Tang, Keqi; Ding, Jie; Shen, Yufeng; Smith, Richard D.

    2008-01-01

    The goal of metabolomics analyses is the detection and quantitation of as many sample components as reasonably possible in order to identify compounds or “features” that can be used to characterize the samples under study. When utilizing electrospray ionization to produce ions for analysis by mass spectrometry (MS), it is important that metabolome sample constituents be efficiently separated prior to ion production, in order to minimize ionization suppression and thereby extend the dynamic range of the measurement, as well as the coverage of the metabolome. Similarly, optimization of the MS inlet and interface can lead to increased measurement sensitivity. This perspective review will focus on the role of high resolution liquid chromatography (LC) separations in conjunction with improved ion production and transmission for LC-MS-based metabolomics. Additional emphasis will be placed on the compromise between metabolome coverage and sample analysis throughput. PMID:19255623

  6. Integration of targeted metabolomics and transcriptomics identifies deregulation of phosphatidylcholine metabolism in Huntington's disease peripheral blood samples.

    PubMed

    Mastrokolias, Anastasios; Pool, Rene; Mina, Eleni; Hettne, Kristina M; van Duijn, Erik; van der Mast, Roos C; van Ommen, GertJan; 't Hoen, Peter A C; Prehn, Cornelia; Adamski, Jerzy; van Roon-Mom, Willeke

    Metabolic changes have been frequently associated with Huntington's disease (HD). At the same time peripheral blood represents a minimally invasive sampling avenue with little distress to Huntington's disease patients especially when brain or other tissue samples are difficult to collect. We investigated the levels of 163 metabolites in HD patient and control serum samples in order to identify disease related changes. Additionally, we integrated the metabolomics data with our previously published next generation sequencing-based gene expression data from the same patients in order to interconnect the metabolomics changes with transcriptional alterations. This analysis was performed using targeted metabolomics and flow injection electrospray ionization tandem mass spectrometry in 133 serum samples from 97 Huntington's disease patients (29 pre-symptomatic and 68 symptomatic) and 36 controls. By comparing HD mutation carriers with controls we identified 3 metabolites significantly changed in HD (serine and threonine and one phosphatidylcholine-PC ae C36:0) and an additional 8 phosphatidylcholines (PC aa C38:6, PC aa C36:0, PC ae C38:0, PC aa C38:0, PC ae C38:6, PC ae C42:0, PC aa C36:5 and PC ae C36:0) that exhibited a significant association with disease severity. Using workflow based exploitation of pathway databases and by integrating our metabolomics data with our gene expression data from the same patients we identified 4 deregulated phosphatidylcholine metabolism related genes ( ALDH1B1 , MBOAT1 , MTRR and PLB1 ) that showed significant association with the changes in metabolite concentrations. Our results support the notion that phosphatidylcholine metabolism is deregulated in HD blood and that these metabolite alterations are associated with specific gene expression changes.

  7. Targeted Metabolomics Identifies Pharmacodynamic Biomarkers for BIO 300 Mitigation of Radiation-Induced Lung Injury.

    PubMed

    Jones, Jace W; Jackson, Isabel L; Vujaskovic, Zeljko; Kaytor, Michael D; Kane, Maureen A

    2017-12-01

    Biomarkers serve a number of purposes during drug development including defining the natural history of injury/disease, serving as a secondary endpoint or trigger for intervention, and/or aiding in the selection of an effective dose in humans. BIO 300 is a patent-protected pharmaceutical formulation of nanoparticles of synthetic genistein being developed by Humanetics Corporation. The primary goal of this metabolomic discovery experiment was to identify biomarkers that correlate with radiation-induced lung injury and BIO 300 efficacy for mitigating tissue damage based upon the primary endpoint of survival. High-throughput targeted metabolomics of lung tissue from male C57L/J mice exposed to 12.5 Gy whole thorax lung irradiation, treated daily with 400 mg/kg BIO 300 for either 2 weeks or 6 weeks starting 24 h post radiation exposure, were assayed at 180 d post-radiation to identify potential biomarkers. A panel of lung metabolites that are responsive to radiation and able to distinguish an efficacious treatment schedule of BIO 300 from a non-efficacious treatment schedule in terms of 180 d survival were identified. These metabolites represent potential biomarkers that could be further validated for use in drug development of BIO 300 and in the translation of dose from animal to human.

  8. Metabolomics for Assessment of Nutritional Status

    PubMed Central

    Zivkovic, Angela M.; German, J. Bruce

    2010-01-01

    Purpose of review The current rise in diet-related diseases continues to be one of the most significant health problems facing both the developed and the developing world. The use of metabolomics – the accurate and comprehensive measurement of a significant fraction of important metabolites in accessible biological fluids – for the assessment of nutritional status, is a promising way forward. The basic toolset, targets, and knowledge are all being developed in the emerging field of metabolomics, yet important knowledge and technology gaps will need to be addressed in order to bring such assessment to practice. Recent findings Dysregulation within the principal metabolic organs (e.g. intestine, adipose, skeletal muscle, liver) are at the center of a diet-disease paradigm that includes metabolic syndrome, type 2 diabetes, and obesity. The assessment of both essential nutrient status, and the more comprehensive systemic metabolic response to dietary, lifestyle, and environmental influences (e.g. metabolic phenotype) are necessary for the evaluation of status in individuals that can identify the multiple targets of intervention needed to address metabolic disease. Summary The first proofs of principle building the knowledge to bring actionable metabolic diagnostics to practice through metabolomics are now appearing. PMID:19584717

  9. GSimp: A Gibbs sampler based left-censored missing value imputation approach for metabolomics studies

    PubMed Central

    Jia, Erik; Chen, Tianlu

    2018-01-01

    Left-censored missing values commonly exist in targeted metabolomics datasets and can be considered as missing not at random (MNAR). Improper data processing procedures for missing values will cause adverse impacts on subsequent statistical analyses. However, few imputation methods have been developed and applied to the situation of MNAR in the field of metabolomics. Thus, a practical left-censored missing value imputation method is urgently needed. We developed an iterative Gibbs sampler based left-censored missing value imputation approach (GSimp). We compared GSimp with other three imputation methods on two real-world targeted metabolomics datasets and one simulation dataset using our imputation evaluation pipeline. The results show that GSimp outperforms other imputation methods in terms of imputation accuracy, observation distribution, univariate and multivariate analyses, and statistical sensitivity. Additionally, a parallel version of GSimp was developed for dealing with large scale metabolomics datasets. The R code for GSimp, evaluation pipeline, tutorial, real-world and simulated targeted metabolomics datasets are available at: https://github.com/WandeRum/GSimp. PMID:29385130

  10. Metabolome analysis of Drosophila melanogaster during embryogenesis.

    PubMed

    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.

  11. Metabolome Analysis of Drosophila melanogaster during Embryogenesis

    PubMed Central

    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. PMID:25121768

  12. Metabolomics studies in brain tissue: A review.

    PubMed

    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.

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

    PubMed

    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

  14. Assessing the impact of transcriptomics, proteomics and metabolomics on fungal phytopathology.

    PubMed

    Tan, Kar-Chun; Ipcho, Simon V S; Trengove, Robert D; Oliver, Richard P; Solomon, Peter S

    2009-09-01

    SUMMARY Peer-reviewed literature is today littered with exciting new tools and techniques that are being used in all areas of biology and medicine. Transcriptomics, proteomics and, more recently, metabolomics are three of these techniques that have impacted on fungal plant pathology. Used individually, each of these techniques can generate a plethora of data that could occupy a laboratory for years. When used in combination, they have the potential to comprehensively dissect a system at the transcriptional and translational level. Transcriptomics, or quantitative gene expression profiling, is arguably the most familiar to researchers in the field of fungal plant pathology. Microarrays have been the primary technique for the last decade, but others are now emerging. Proteomics has also been exploited by the fungal phytopathogen community, but perhaps not to its potential. A lack of genome sequence information has frustrated proteomics researchers and has largely contributed to this technique not fulfilling its potential. The coming of the genome sequencing era has partially alleviated this problem. Metabolomics is the most recent of these techniques to emerge and is concerned with the non-targeted profiling of all metabolites in a given system. Metabolomics studies on fungal plant pathogens are only just beginning to appear, although its potential to dissect many facets of the pathogen and disease will see its popularity increase quickly. This review assesses the impact of transcriptomics, proteomics and metabolomics on fungal plant pathology over the last decade and discusses their futures. Each of the techniques is described briefly with further reading recommended. Key examples highlighting the application of these technologies to fungal plant pathogens are also reviewed.

  15. Recent advances in the application of metabolomics to Alzheimer's Disease.

    PubMed

    Trushina, Eugenia; Mielke, Michelle M

    2014-08-01

    The pathophysiological changes associated with Alzheimer's Disease (AD) begin decades before the emergence of clinical symptoms. Understanding the early mechanisms associated with AD pathology is, therefore, especially important for identifying disease-modifying therapeutic targets. While the majority of AD clinical trials to date have focused on anti-amyloid-beta (Aβ) treatments, other therapeutic approaches may be necessary. The ability to monitor changes in cellular networks that include both Aβ and non-Aβ pathways is essential to advance our understanding of the etiopathogenesis of AD and subsequent development of cognitive symptoms and dementia. Metabolomics is a powerful tool that detects perturbations in the metabolome, a pool of metabolites that reflects changes downstream of genomic, transcriptomic and proteomic fluctuations, and represents an accurate biochemical profile of the organism in health and disease. The application of metabolomics could help to identify biomarkers for early AD diagnosis, to discover novel therapeutic targets, and to monitor therapeutic response and disease progression. Moreover, given the considerable parallel between mouse and human metabolism, the use of metabolomics provides ready translation of animal research into human studies for accelerated drug design. In this review, we will summarize current progress in the application of metabolomics in both animal models and in humans to further understanding of the mechanisms involved in AD pathogenesis. © 2013.

  16. Global metabolomic profiling targeting childhood obesity in the Hispanic population

    USDA-ARS?s Scientific Manuscript database

    Metabolomics may unravel important biological pathways involved in the pathophysiology of childhood obesity. We aimed to 1) identify metabolites that differ significantly between nonobese and obese Hispanic children; 2) collapse metabolites into principal components (PCs) associated with obesity and...

  17. Targeted metabolomics reveals reduced levels of polyunsaturated choline plasmalogens and a smaller dimethylarginine/arginine ratio in the follicular fluid of patients with a diminished ovarian reserve.

    PubMed

    de la Barca, J M Chao; Boueilh, T; Simard, G; Boucret, L; Ferré-L'Hotellier, V; Tessier, L; Gadras, C; Bouet, P E; Descamps, P; Procaccio, V; Reynier, P; May-Panloup, P

    2017-11-01

    Does the metabolomic profile of the follicular fluid (FF) of patients with a diminished ovarian reserve (DOR) differ from that of patients with a normal ovarian reserve (NOR)? The metabolomic signature of the FF reveals a significant decrease in polyunsaturated choline plasmalogens and methyl arginine transferase activity in DOR patients compared to NOR patients. The composition of the FF reflects the exchanges between the oocyte and its microenvironment during its acquisition of gametic competence. Studies of the FF have allowed identification of biomarkers and metabolic pathways involved in various pathologies affecting oocyte quality, but no large metabolomic analysis in the context of ovarian ageing and DOR has been undertaken so far. This was an observational study of the FF retrieved from 57 women undergoing in vitro fertilization at the University Hospital of Angers, France, from November 2015 to September 2016. The women were classified in two groups: one including 28 DOR patients, and the other including 29 NOR patients, serving as controls. Patients were enrolled in the morning of oocyte retrieval after ovarian stimulation. Once the oocytes were isolated for fertilization and culture, the FF was pooled and centrifuged for analysis. A targeted quantitative metabolomic analysis was performed using high-performance liquid chromatography coupled with tandem mass spectrometry, and the Biocrates Absolute IDQ p180 kit. The FF levels of 188 metabolites and several sums and ratios of metabolic significance were assessed by multivariate and univariate analyses. A total of 136 metabolites were accurately quantified and used for calculating 23 sums and ratios. Samples were randomly divided into training and validation sets. The training set, allowed the construction of multivariate statistical models with a projection-supervised method, i.e. orthogonal partial least squares discriminant analysis (OPLS-DA), applied to the full set of metabolites, or the penalized

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

    PubMed

    Salek, Reza M; Neumann, Steffen; Schober, Daniel; Hummel, Jan; Billiau, Kenny; Kopka, Joachim; Correa, Elon; Reijmers, Theo; Rosato, Antonio; Tenori, Leonardo; Turano, Paola; Marin, Silvia; Deborde, Catherine; Jacob, Daniel; Rolin, Dominique; Dartigues, Benjamin; Conesa, Pablo; Haug, Kenneth; Rocca-Serra, Philippe; O'Hagan, Steve; Hao, Jie; van Vliet, Michael; Sysi-Aho, Marko; Ludwig, Christian; Bouwman, Jildau; Cascante, Marta; Ebbels, Timothy; Griffin, Julian L; Moing, Annick; Nikolski, Macha; Oresic, Matej; Sansone, Susanna-Assunta; Viant, Mark R; Goodacre, Royston; Günther, Ulrich L; Hankemeier, Thomas; Luchinat, Claudio; Walther, Dirk; Steinbeck, Christoph

    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 funders. After the initial efforts of the metabolomics standards initiative, minimum reporting standards were proposed which included the concepts for metabolomics databases. Built by the community, standards and infrastructure for metabolomics are still needed to allow storage, exchange, comparison and re-utilization of metabolomics data. The Framework Programme 7 EU Initiative 'coordination of standards in metabolomics' (COSMOS) is developing a robust data infrastructure and exchange standards for metabolomics data and metadata. This is to support workflows for a broad range of metabolomics applications within the European metabolomics community and the wider metabolomics and biomedical communities' participation. Here we announce our concepts and efforts asking for re-engagement of the metabolomics community, academics and industry, journal publishers, software and hardware vendors, as well as those interested in standardisation worldwide (addressing missing metabolomics ontologies, complex-metadata capturing and XML based open source data exchange format), to join and work towards updating and implementing metabolomics standards.

  19. Metabolomics: Insulin Resistance and Type 2 Diabetes Mellitus

    USDA-ARS?s Scientific Manuscript database

    Type 2 diabetes mellitus (T2DM) develops over many years, providing an opportunity to consider early prognostic tools that guide interventions to thwart disease. Advancements in analytical chemistry enable quantitation of hundreds of metabolites in biofluids and tissues (metabolomics), providing in...

  20. Targeted metabolomics: new insights into pathobiology of retained placenta in dairy cows and potential risk biomarkers.

    PubMed

    Dervishi, E; Zhang, G; Mandal, R; Wishart, D S; Ametaj, B N

    2018-05-01

    A targeted quantitative metabolomics approach was used to study temporal changes of serum metabolites in cows that normally released their fetal membranes and those that retained the placenta. We identified and measured serum concentrations of 128 metabolites including amino acids, acylcarnitines, biogenic amines, glycerophospholipids, sphingolipids and hexose at -8 and -4 weeks before parturition, during the week of retained placenta (RP) diagnosis, and at +4 and +8 weeks after parturition. In addition, we aimed at identifying metabolite signatures of pre-RP in the serum that might be used as predictive biomarkers for risk of developing RP in dairy cows. Results revealed major alterations in the metabolite fingerprints of pre-RP cows starting as early as -8 weeks before parturition and continuing as far as +8 weeks after calving. Biomarker candidates found in this study are mainly biomarkers of inflammation which might not be specific to RP. Therefore, the relevance of serum Lys, Orn, acetylornithine, lysophophatidylcholine LysoPC a C28:0, Asp, Leu and Ile as potential serum biomarkers for prediction of risk of RP in dairy cows will have to be tested in the future. In addition, lower concentrations of LysoPCs, Trp, and higher kynurenine in the serum during prepartum and the week of occurrence of RP suggest involvement of inflammation in the pathobiology of RP.

  1. Non-targeted metabolomic approach reveals urinary metabolites linked to steroid biosynthesis pathway after ingestion of citrus juice.

    PubMed

    Medina, S; Ferreres, F; García-Viguera, C; Horcajada, M N; Orduna, J; Savirón, M; Zurek, G; Martínez-Sanz, J M; Gil, J I; Gil-Izquierdo, A

    2013-01-15

    Citrus juice intake has been highlighted because of its health-promoting effects. LC-MS based metabolomics approaches are applied to obtain a better knowledge on changes in the concentration of metabolites due to its dietary intake and allow a better understanding of involved metabolic pathways. Eight volunteers daily consumed 400 mL of juice for four consecutive days and urine samples were collected before intake and 24h after each citrus juice intake. Urine samples were analysed by nanoHPLC-q-TOF, followed by principal component analysis (PCA) and Student's t-test (p<0.05). PCA showed a separation between two groups (before and after citrus juice consumption). This approach allowed the identification of four endocrine compounds (tetrahydroaldosterone-3-glucuronide, cortolone-3-glucuronide, testosterone-glucuronide and 17-hydroxyprogesterone), which belonged to the steroid biosynthesis pathway as significant metabolites upregulated by citrus juice intake. Additionally, these results confirmed the importance of using the non-targeted metabolomics technique to identify new endogenous metabolites, up- or down-regulated as a consequence of food intake. Copyright © 2012 Elsevier Ltd. All rights reserved.

  2. Metabolomics window into diabetic complications.

    PubMed

    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.

  3. MetaboLights: An Open-Access Database Repository for Metabolomics Data.

    PubMed

    Kale, Namrata S; Haug, Kenneth; Conesa, Pablo; Jayseelan, Kalaivani; Moreno, Pablo; Rocca-Serra, Philippe; Nainala, Venkata Chandrasekhar; Spicer, Rachel A; Williams, Mark; Li, Xuefei; Salek, Reza M; Griffin, Julian L; Steinbeck, Christoph

    2016-03-24

    MetaboLights is the first general purpose, open-access database repository for cross-platform and cross-species metabolomics research at the European Bioinformatics Institute (EMBL-EBI). Based upon the open-source ISA framework, MetaboLights provides Metabolomics Standard Initiative (MSI) compliant metadata and raw experimental data associated with metabolomics experiments. Users can upload their study datasets into the MetaboLights Repository. These studies are then automatically assigned a stable and unique identifier (e.g., MTBLS1) that can be used for publication reference. The MetaboLights Reference Layer associates metabolites with metabolomics studies in the archive and is extensively annotated with data fields such as structural and chemical information, NMR and MS spectra, target species, metabolic pathways, and reactions. The database is manually curated with no specific release schedules. MetaboLights is also recommended by journals for metabolomics data deposition. This unit provides a guide to using MetaboLights, downloading experimental data, and depositing metabolomics datasets using user-friendly submission tools. Copyright © 2016 John Wiley & Sons, Inc.

  4. Metabolomics for Plant Improvement: Status and Prospects

    PubMed Central

    Kumar, Rakesh; Bohra, Abhishek; Pandey, Arun K.; Pandey, Manish K.; Kumar, Anirudh

    2017-01-01

    Post-genomics era has witnessed the development of cutting-edge technologies that have offered cost-efficient and high-throughput ways for molecular characterization of the function of a cell or organism. Large-scale metabolite profiling assays have allowed researchers to access the global data sets of metabolites and the corresponding metabolic pathways in an unprecedented way. Recent efforts in metabolomics have been directed to improve the quality along with a major focus on yield related traits. Importantly, an integration of metabolomics with other approaches such as quantitative genetics, transcriptomics and genetic modification has established its immense relevance to plant improvement. An effective combination of these modern approaches guides researchers to pinpoint the functional gene(s) and the characterization of massive metabolites, in order to prioritize the candidate genes for downstream analyses and ultimately, offering trait specific markers to improve commercially important traits. This in turn will improve the ability of a plant breeder by allowing him to make more informed decisions. Given this, the present review captures the significant leads gained in the past decade in the field of plant metabolomics accompanied by a brief discussion on the current contribution and the future scope of metabolomics to accelerate plant improvement. PMID:28824660

  5. Review of mass spectrometry-based metabolomics in cancer research

    PubMed Central

    Liesenfeld, David B.; Habermann, Nina; Owen, Robert W.; Scalbert, Augustin; Ulrich, Cornelia M.

    2014-01-01

    Metabolomics, the systematic investigation of all metabolites present within a biological system, is used in biomarker development for many human diseases, including cancer. In this review we investigate the current role of mass spectrometry-based metabolomics in cancer research. A literature review was carried out within the databases PubMed, Embase and Web of Knowledge. We included 106 studies reporting on 21 different types of cancer in 7 different sample types. Metabolomics in cancer research is most often used for case-control comparisons. Secondary applications include translational areas, such as patient prognosis, therapy control and tumor classification or grading. Metabolomics is at a developmental stage with respect to epidemiology, with the majority of studies including <100 patients. Standardization is required especially concerning sample preparation and data analysis. In a second part of this review, we reconstructed a metabolic network of cancer patients by quantitatively extracting all reports of altered metabolites: Alterations in energy metabolism, membrane and fatty acid synthesis emerged, with tryptophan levels changed most frequently in various cancers. Metabolomics has the potential to evolve into a standard tool for future applications in epidemiology and translational cancer research, but further, large-scale studies including prospective validation are needed. PMID:24096148

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

    PubMed

    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.

  7. Metabolic engineering of a tyrosine-overproducing yeast platform using targeted metabolomics.

    PubMed

    Gold, Nicholas D; Gowen, Christopher M; Lussier, Francois-Xavier; Cautha, Sarat C; Mahadevan, Radhakrishnan; Martin, Vincent J J

    2015-05-28

    L-tyrosine is a common precursor for a wide range of valuable secondary metabolites, including benzylisoquinoline alkaloids (BIAs) and many polyketides. An industrially tractable yeast strain optimized for production of L-tyrosine could serve as a platform for the development of BIA and polyketide cell factories. This study applied a targeted metabolomics approach to evaluate metabolic engineering strategies to increase the availability of intracellular L-tyrosine in the yeast Saccharomyces cerevisiae CEN.PK. Our engineering strategies combined localized pathway engineering with global engineering of central metabolism, facilitated by genome-scale steady-state modelling. Addition of a tyrosine feedback resistant version of 3-deoxy-D-arabino-heptulosonate-7-phosphate synthase Aro4 from S. cerevisiae was combined with overexpression of either a tyrosine feedback resistant yeast chorismate mutase Aro7, the native pentafunctional arom protein Aro1, native prephenate dehydrogenase Tyr1 or cyclohexadienyl dehydrogenase TyrC from Zymomonas mobilis. Loss of aromatic carbon was limited by eliminating phenylpyruvate decarboxylase Aro10. The TAL gene from Rhodobacter sphaeroides was used to produce coumarate as a simple test case of a heterologous by-product of tyrosine. Additionally, multiple strategies for engineering global metabolism to promote tyrosine production were evaluated using metabolic modelling. The T21E mutant of pyruvate kinase Cdc19 was hypothesized to slow the conversion of phosphoenolpyruvate to pyruvate and accumulate the former as precursor to the shikimate pathway. The ZWF1 gene coding for glucose-6-phosphate dehydrogenase was deleted to create an NADPH deficiency designed to force the cell to couple its growth to tyrosine production via overexpressed NADP(+)-dependent prephenate dehydrogenase Tyr1. Our engineered Zwf1(-) strain expressing TYRC ARO4(FBR) and grown in the presence of methionine achieved an intracellular L-tyrosine accumulation up to 520

  8. Quantitative Clinical Diagnostic Analysis of Acetone in Human Blood by HPLC: A Metabolomic Search for Acetone as Indicator

    PubMed Central

    Akgul Kalkan, Esin; Sahiner, Mehtap; Ulker Cakir, Dilek; Alpaslan, Duygu; Yilmaz, Selehattin

    2016-01-01

    Using high-performance liquid chromatography (HPLC) and 2,4-dinitrophenylhydrazine (2,4-DNPH) as a derivatizing reagent, an analytical method was developed for the quantitative determination of acetone in human blood. The determination was carried out at 365 nm using an ultraviolet-visible (UV-Vis) diode array detector (DAD). For acetone as its 2,4-dinitrophenylhydrazone derivative, a good separation was achieved with a ThermoAcclaim C18 column (15 cm × 4.6 mm × 3 μm) at retention time (t R) 12.10 min and flowrate of 1 mL min−1 using a (methanol/acetonitrile) water elution gradient. The methodology is simple, rapid, sensitive, and of low cost, exhibits good reproducibility, and allows the analysis of acetone in biological fluids. A calibration curve was obtained for acetone using its standard solutions in acetonitrile. Quantitative analysis of acetone in human blood was successfully carried out using this calibration graph. The applied method was validated in parameters of linearity, limit of detection and quantification, accuracy, and precision. We also present acetone as a useful tool for the HPLC-based metabolomic investigation of endogenous metabolism and quantitative clinical diagnostic analysis. PMID:27298750

  9. Distinct urine metabolome after Asian ginseng and American ginseng intervention based on GC-MS metabolomics approach

    PubMed Central

    Yang, Liu; Yu, Qing-Tao; Ge, Ya-Zhong; Zhang, Wen-Song; Fan, Yong; Ma, Chung-Wah; Liu, Qun; Qi, Lian-Wen

    2016-01-01

    Ginseng occupies a prominent position in the list of best-selling natural products worldwide. Asian ginseng (Panax ginseng) and American ginseng (Panax quinquefolius) show different properties and medicinal applications in pharmacology, even though the main active constituents of them are both thought to be ginsenosides. Metabolomics is a promising method to profile entire endogenous metabolites and monitor their fluctuations related to exogenous stimulus. Herein, an untargeted metabolomics approach was applied to study the overall urine metabolic differences between Asian ginseng and American ginseng in mice. Metabolomics analyses were performed using gas chromatography-mass spectrometry (GC-MS) together with multivariate statistical data analysis. A total of 21 metabolites related to D-glutamine and D-glutamate metabolism, glutathione metabolism, TCA cycle and glyoxylate and dicarboxylate metabolism, differed significantly under the Asian ginseng treatment; 34 metabolites mainly associated with glyoxylate and dicarboxylate metabolism, TCA cycle and taurine and hypotaurine metabolism, were significantly altered after American ginseng treatment. Urinary metabolomics reveal that Asian ginseng and American ginseng can benefit organism physiological and biological functions via regulating multiple metabolic pathways. The important pathways identified from Asian ginseng and American ginseng can also help to explore new therapeutic effects or action targets so as to broad application of these two ginsengs. PMID:27991533

  10. An initial non-targeted analysis of the peanut seed metabolome

    USDA-ARS?s Scientific Manuscript database

    There are likely a large number of compounds that constitute the peanut seed metabolome that have yet to be elucidated. Although the proximate composition and nutrients such as vitamins and minerals are well known, the composition of many other small molecule metabolites present have not been syste...

  11. Quantitative self-assembly prediction yields targeted nanomedicines

    NASA Astrophysics Data System (ADS)

    Shamay, Yosi; Shah, Janki; Işık, Mehtap; Mizrachi, Aviram; Leibold, Josef; Tschaharganeh, Darjus F.; Roxbury, Daniel; Budhathoki-Uprety, Januka; Nawaly, Karla; Sugarman, James L.; Baut, Emily; Neiman, Michelle R.; Dacek, Megan; Ganesh, Kripa S.; Johnson, Darren C.; Sridharan, Ramya; Chu, Karen L.; Rajasekhar, Vinagolu K.; Lowe, Scott W.; Chodera, John D.; Heller, Daniel A.

    2018-02-01

    Development of targeted nanoparticle drug carriers often requires complex synthetic schemes involving both supramolecular self-assembly and chemical modification. These processes are generally difficult to predict, execute, and control. We describe herein a targeted drug delivery system that is accurately and quantitatively predicted to self-assemble into nanoparticles based on the molecular structures of precursor molecules, which are the drugs themselves. The drugs assemble with the aid of sulfated indocyanines into particles with ultrahigh drug loadings of up to 90%. We devised quantitative structure-nanoparticle assembly prediction (QSNAP) models to identify and validate electrotopological molecular descriptors as highly predictive indicators of nano-assembly and nanoparticle size. The resulting nanoparticles selectively targeted kinase inhibitors to caveolin-1-expressing human colon cancer and autochthonous liver cancer models to yield striking therapeutic effects while avoiding pERK inhibition in healthy skin. This finding enables the computational design of nanomedicines based on quantitative models for drug payload selection.

  12. Tissue Multiplatform-Based Metabolomics/Metabonomics for Enhanced Metabolome Coverage.

    PubMed

    Vorkas, Panagiotis A; Abellona U, M R; Li, Jia V

    2018-01-01

    The use of tissue as a matrix to elucidate disease pathology or explore intervention comes with several advantages. It allows investigation of the target alteration directly at the focal location and facilitates the detection of molecules that could become elusive after secretion into biofluids. However, tissue metabolomics/metabonomics comes with challenges not encountered in biofluid analyses. Furthermore, tissue heterogeneity does not allow for tissue aliquoting. Here we describe a multiplatform, multi-method workflow which enables metabolic profiling analysis of tissue samples, while it can deliver enhanced metabolome coverage. After applying a dual consecutive extraction (organic followed by aqueous), tissue extracts are analyzed by reversed-phase (RP-) and hydrophilic interaction liquid chromatography (HILIC-) ultra-performance liquid chromatography coupled to mass spectrometry (UPLC-MS) and nuclear magnetic resonance (NMR) spectroscopy. This pipeline incorporates the required quality control features, enhances versatility, allows provisional aliquoting of tissue extracts for future guided analyses, expands the range of metabolites robustly detected, and supports data integration. It has been successfully employed for the analysis of a wide range of tissue types.

  13. Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics

    PubMed Central

    Giacomoni, Franck; Le Corguillé, Gildas; Monsoor, Misharl; Landi, Marion; Pericard, Pierre; Pétéra, Mélanie; Duperier, Christophe; Tremblay-Franco, Marie; Martin, Jean-François; Jacob, Daniel; Goulitquer, Sophie; Thévenot, Etienne A.; Caron, Christophe

    2015-01-01

    Summary: The complex, rapidly evolving field of computational metabolomics calls for collaborative infrastructures where the large volume of new algorithms for data pre-processing, statistical analysis and annotation can be readily integrated whatever the language, evaluated on reference datasets and chained to build ad hoc workflows for users. We have developed Workflow4Metabolomics (W4M), the first fully open-source and collaborative online platform for computational metabolomics. W4M is a virtual research environment built upon the Galaxy web-based platform technology. It enables ergonomic integration, exchange and running of individual modules and workflows. Alternatively, the whole W4M framework and computational tools can be downloaded as a virtual machine for local installation. Availability and implementation: http://workflow4metabolomics.org homepage enables users to open a private account and access the infrastructure. W4M is developed and maintained by the French Bioinformatics Institute (IFB) and the French Metabolomics and Fluxomics Infrastructure (MetaboHUB). Contact: contact@workflow4metabolomics.org PMID:25527831

  14. Advances in metabolomic applications in plant genetics and breeding

    USDA-ARS?s Scientific Manuscript database

    Metabolomics is a systems biology discipline wherein abundances of endogenous metabolites from biological samples are identified and quantitatively measured across a large range of metabolites and/or a large number of samples. Since all developmental, physiological and response to the environment ph...

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

    PubMed Central

    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

  16. The Development of Metabolomic Sampling Procedures for Pichia pastoris, and Baseline Metabolome Data

    PubMed Central

    Tredwell, Gregory D.; Edwards-Jones, Bryn; Leak, David J.; Bundy, Jacob G.

    2011-01-01

    Metabolic profiling is increasingly being used to investigate a diverse range of biological questions. Due to the rapid turnover of intracellular metabolites it is important to have reliable, reproducible techniques for sampling and sample treatment. Through the use of non-targeted analytical techniques such as NMR and GC-MS we have performed a comprehensive quantitative investigation of sampling techniques for Pichia pastoris. It was clear that quenching metabolism using solutions based on the standard cold methanol protocol caused some metabolite losses from P. pastoris cells. However, these were at a low level, with the NMR results indicating metabolite increases in the quenching solution below 5% of their intracellular level for 75% of metabolites identified; while the GC-MS results suggest a slightly higher level with increases below 15% of their intracellular values. There were subtle differences between the four quenching solutions investigated but broadly, they all gave similar results. Total culture extraction of cells + broth using high cell density cultures typical of P. pastoris fermentations, was an efficient sampling technique for NMR analysis and provided a gold standard of intracellular metabolite levels; however, salts in the media affected the GC-MS analysis. Furthermore, there was no benefit in including an additional washing step in the quenching process, as the results were essentially identical to those obtained just by a single centrifugation step. We have identified the major high-concentration metabolites found in both the extra- and intracellular locations of P. pastoris cultures by NMR spectroscopy and GC-MS. This has provided us with a baseline metabolome for P. pastoris for future studies. The P. pastoris metabolome is significantly different from that of Saccharomyces cerevisiae, with the most notable difference being the production of high concentrations of arabitol by P. pastoris. PMID:21283710

  17. Targeted Quantitation of Proteins by Mass Spectrometry

    PubMed Central

    2013-01-01

    Quantitative measurement of proteins is one of the most fundamental analytical tasks in a biochemistry laboratory, but widely used immunochemical methods often have limited specificity and high measurement variation. In this review, we discuss applications of multiple-reaction monitoring (MRM) mass spectrometry, which allows sensitive, precise quantitative analyses of peptides and the proteins from which they are derived. Systematic development of MRM assays is permitted by databases of peptide mass spectra and sequences, software tools for analysis design and data analysis, and rapid evolution of tandem mass spectrometer technology. Key advantages of MRM assays are the ability to target specific peptide sequences, including variants and modified forms, and the capacity for multiplexing that allows analysis of dozens to hundreds of peptides. Different quantitative standardization methods provide options that balance precision, sensitivity, and assay cost. Targeted protein quantitation by MRM and related mass spectrometry methods can advance biochemistry by transforming approaches to protein measurement. PMID:23517332

  18. Targeted quantitation of proteins by mass spectrometry.

    PubMed

    Liebler, Daniel C; Zimmerman, Lisa J

    2013-06-04

    Quantitative measurement of proteins is one of the most fundamental analytical tasks in a biochemistry laboratory, but widely used immunochemical methods often have limited specificity and high measurement variation. In this review, we discuss applications of multiple-reaction monitoring (MRM) mass spectrometry, which allows sensitive, precise quantitative analyses of peptides and the proteins from which they are derived. Systematic development of MRM assays is permitted by databases of peptide mass spectra and sequences, software tools for analysis design and data analysis, and rapid evolution of tandem mass spectrometer technology. Key advantages of MRM assays are the ability to target specific peptide sequences, including variants and modified forms, and the capacity for multiplexing that allows analysis of dozens to hundreds of peptides. Different quantitative standardization methods provide options that balance precision, sensitivity, and assay cost. Targeted protein quantitation by MRM and related mass spectrometry methods can advance biochemistry by transforming approaches to protein measurement.

  19. Nutritional metabolomics: Progress in addressing complexity in diet and health

    PubMed Central

    Jones, Dean P.; Park, Youngja; Ziegler, Thomas R.

    2013-01-01

    Nutritional metabolomics is rapidly maturing to use small molecule chemical profiling to support integration of diet and nutrition in complex biosystems research. These developments are critical to facilitate transition of nutritional sciences from population-based to individual-based criteria for nutritional research, assessment and management. This review addresses progress in making these approaches manageable for nutrition research. Important concept developments concerning the exposome, predictive health and complex pathobiology, serve to emphasize the central role of diet and nutrition in integrated biosystems models of health and disease. Improved analytic tools and databases for targeted and non-targeted metabolic profiling, along with bioinformatics, pathway mapping and computational modeling, are now used for nutrition research on diet, metabolism, microbiome and health associations. These new developments enable metabolome-wide association studies (MWAS) and provide a foundation for nutritional metabolomics, along with genomics, epigenomics and health phenotyping, to support integrated models required for personalized diet and nutrition forecasting. PMID:22540256

  20. A Metabolomic Approach to Target Compounds from the Asteraceae Family for Dual COX and LOX Inhibition

    PubMed Central

    Chagas-Paula, Daniela A.; Zhang, Tong; Da Costa, Fernando B.; Edrada-Ebel, RuAngelie

    2015-01-01

    The application of metabolomics in phytochemical analysis is an innovative strategy for targeting active compounds from a complex plant extract. Species of the Asteraceae family are well-known to exhibit potent anti-inflammatory (AI) activity. Dual inhibition of the enzymes COX-1 and 5-LOX is essential for the treatment of several inflammatory diseases, but there is not much investigation reported in the literature for natural products. In this study, 57 leaf extracts (EtOH-H2O 7:3, v/v) from different genera and species of the Asteraceae family were tested against COX-1 and 5-LOX while HPLC-ESI-HRMS analysis of the extracts indicated high diversity in their chemical compositions. Using O2PLS-DA (R2 > 0.92; VIP > 1 and positive Y-correlation values), dual inhibition potential of low-abundance metabolites was determined. The O2PLS-DA results exhibited good validation values (cross-validation = Q2 > 0.7 and external validation = P2 > 0.6) with 0% of false positive predictions. The metabolomic approach determined biomarkers for the required biological activity and detected active compounds in the extracts displaying unique mechanisms of action. In addition, the PCA data also gave insights on the chemotaxonomy of the family Asteraceae across its diverse range of genera and tribes. PMID:26184333

  1. Workflow4Metabolomics: a collaborative research infrastructure for computational metabolomics.

    PubMed

    Giacomoni, Franck; Le Corguillé, Gildas; Monsoor, Misharl; Landi, Marion; Pericard, Pierre; Pétéra, Mélanie; Duperier, Christophe; Tremblay-Franco, Marie; Martin, Jean-François; Jacob, Daniel; Goulitquer, Sophie; Thévenot, Etienne A; Caron, Christophe

    2015-05-01

    The complex, rapidly evolving field of computational metabolomics calls for collaborative infrastructures where the large volume of new algorithms for data pre-processing, statistical analysis and annotation can be readily integrated whatever the language, evaluated on reference datasets and chained to build ad hoc workflows for users. We have developed Workflow4Metabolomics (W4M), the first fully open-source and collaborative online platform for computational metabolomics. W4M is a virtual research environment built upon the Galaxy web-based platform technology. It enables ergonomic integration, exchange and running of individual modules and workflows. Alternatively, the whole W4M framework and computational tools can be downloaded as a virtual machine for local installation. http://workflow4metabolomics.org homepage enables users to open a private account and access the infrastructure. W4M is developed and maintained by the French Bioinformatics Institute (IFB) and the French Metabolomics and Fluxomics Infrastructure (MetaboHUB). contact@workflow4metabolomics.org. © The Author 2014. Published by Oxford University Press.

  2. Development of a universal metabolome-standard method for long-term LC-MS metabolome profiling and its application for bladder cancer urine-metabolite-biomarker discovery.

    PubMed

    Peng, Jun; Chen, Yi-Ting; Chen, Chien-Lun; Li, Liang

    2014-07-01

    Large-scale metabolomics study requires a quantitative method to generate metabolome data over an extended period with high technical reproducibility. We report a universal metabolome-standard (UMS) method, in conjunction with chemical isotope labeling liquid chromatography-mass spectrometry (LC-MS), to provide long-term analytical reproducibility and facilitate metabolome comparison among different data sets. In this method, UMS of a specific type of sample labeled by an isotope reagent is prepared a priori. The UMS is spiked into any individual samples labeled by another form of the isotope reagent in a metabolomics study. The resultant mixture is analyzed by LC-MS to provide relative quantification of the individual sample metabolome to UMS. UMS is independent of a study undertaking as well as the time of analysis and useful for profiling the same type of samples in multiple studies. In this work, the UMS method was developed and applied for a urine metabolomics study of bladder cancer. UMS of human urine was prepared by (13)C2-dansyl labeling of a pooled sample from 20 healthy individuals. This method was first used to profile the discovery samples to generate a list of putative biomarkers potentially useful for bladder cancer detection and then used to analyze the verification samples about one year later. Within the discovery sample set, three-month technical reproducibility was examined using a quality control sample and found a mean CV of 13.9% and median CV of 9.4% for all the quantified metabolites. Statistical analysis of the urine metabolome data showed a clear separation between the bladder cancer group and the control group from the discovery samples, which was confirmed by the verification samples. Receiver operating characteristic (ROC) test showed that the area under the curve (AUC) was 0.956 in the discovery data set and 0.935 in the verification data set. These results demonstrated the utility of the UMS method for long-term metabolomics and

  3. Metabolomic signature of brain cancer.

    PubMed

    Pandey, Renu; Caflisch, Laura; Lodi, Alessia; Brenner, Andrew J; Tiziani, Stefano

    2017-11-01

    Despite advances in surgery and adjuvant therapy, brain tumors represent one of the leading causes of cancer-related mortality and morbidity in both adults and children. Gliomas constitute about 60% of all cerebral tumors, showing varying degrees of malignancy. They are difficult to treat due to dismal prognosis and limited therapeutics. Metabolomics is the untargeted and targeted analyses of endogenous and exogenous small molecules, which charact erizes the phenotype of an individual. This emerging "omics" science provides functional readouts of cellular activity that contribute greatly to the understanding of cancer biology including brain tumor biology. Metabolites are highly informative as a direct signature of biochemical activity; therefore, metabolite profiling has become a promising approach for clinical diagnostics and prognostics. The metabolic alterations are well-recognized as one of the key hallmarks in monitoring disease progression, therapy, and revealing new molecular targets for effective therapeutic intervention. Taking advantage of the latest high-throughput analytical technologies, that is, nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), metabolomics is now a promising field for precision medicine and drug discovery. In the present report, we review the application of metabolomics and in vivo metabolic profiling in the context of adult gliomas and paediatric brain tumors. Analytical platforms such as high-resolution (HR) NMR, in vivo magnetic resonance spectroscopic imaging and high- and low-resolution MS are discussed. Moreover, the relevance of metabolic studies in the development of new therapeutic strategies for treatment of gliomas are reviewed. © 2017 Wiley Periodicals, Inc.

  4. Applying quantitative metabolomics based on chemical isotope labeling LC-MS for detecting potential milk adulterant in human milk.

    PubMed

    Mung, Dorothea; Li, Liang

    2018-02-25

    There is an increasing demand for donor human milk to feed infants for various reasons including that a mother may be unable to provide sufficient amounts of milk for their child or the milk is considered unsafe for the baby. Selling and buying human milk via the Internet has gained popularity. However, there is a risk of human milk sold containing other adulterants such as animal or plant milk. Analytical tools for rapid detection of adulterants in human milk are needed. We report a quantitative metabolomics method for detecting potential milk adulterants (soy, almond, cow, goat and infant formula milk) in human milk. It is based on the use of a high-performance chemical isotope labeling (CIL) LC-MS platform to profile the metabolome of an unknown milk sample, followed by multivariate or univariate comparison of the resultant metabolomic profile with that of human milk to determine the differences. Using dansylation LC-MS to profile the amine/phenol submetabolome, we could detect an average of 4129 ± 297 (n = 9) soy metabolites, 3080 ± 470 (n = 9) almond metabolites, 4256 ± 136 (n = 18) cow metabolites, 4318 ± 198 (n = 9) goat metabolites, 4444 ± 563 (n = 9) infant formula metabolites, and 4020 ± 375 (n = 30) human metabolites. This high level of coverage allowed us to readily differentiate the six different types of samples. From the analysis of binary mixtures of human milk containing 5, 10, 25, 50 and 75% other type of milk, we demonstrated that this method could be used to detect the presence of as low as 5% adulterant in human milk. We envisage that this method could be applied to detect contaminant or adulterant in other types of food or drinks. Copyright © 2017 Elsevier B.V. All rights reserved.

  5. Metabolomics: A Primer.

    PubMed

    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.

  6. Metabolomics for laboratory diagnostics.

    PubMed

    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.

  7. Metabolic screening and metabolomics analysis in the Intellectual Developmental Disorders Mexico Study.

    PubMed

    Ibarra-González, Isabel; Rodríguez-Valentín, Rocío; Lazcano-Ponce, Eduardo; Vela-Amieva, Marcela

    2017-01-01

    Inborn errors of metabolism (IEM) are genetic conditions that are sometimes associated with intellectual developmental disorders (IDD). The aim of this study is to contribute to the metabolic characterization of IDD of unknown etiology in Mexico. Metabolic screening using tandem mass spectrometry and fluorometry will be performed to rule out IEM. In addition, target metabolomic analysis will be done to characterize the metabolomic profile of patients with IDD. Identification of new metabolomic profiles associated with IDD of unknown etiology and comorbidities will contribute to the development of novel diagnostic and therapeutic schemes for the prevention and treatment of IDD in Mexico.

  8. The application of skin metabolomics in the context of transdermal drug delivery.

    PubMed

    Li, Jinling; Xu, Weitong; Liang, Yibiao; Wang, Hui

    2017-04-01

    Metabolomics is a powerful emerging tool for the identification of biomarkers and the exploration of metabolic pathways in a high-throughput manner. As an administration site for percutaneous absorption, the skin has a variety of metabolic enzymes, except other than hepar. However, technologies to fully detect dermal metabolites remain lacking. Skin metabolomics studies have mainly focused on the regulation of dermal metabolites by drugs or on the metabolism of drugs themselves. Skin metabolomics techniques include collection and preparation of skin samples, data collection, data processing and analysis. Furthermore, studying dermal metabolic effects via metabolomics can provide novel explanations for the pathogenesis of some dermatoses and unique insights for designing targeted prodrugs, promoting drug absorption and controlling drug concentration. This paper reviews current progress in the field of skin metabolomics, with a specific focus on dermal drug delivery systems and dermatosis. Copyright © 2016. Published by Elsevier Urban & Partner Sp. z o.o.

  9. 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.

    PubMed

    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 (RSD<15%). The method was then satisfactorily applied to more widely analyze the small molecules metabolome 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.

  10. Phenolic and microbial-targeted metabolomics to discovering and evaluating wine intake biomarkers in human urine and plasma.

    PubMed

    Urpi-Sarda, Mireia; Boto-Ordóñez, María; Queipo-Ortuño, María Isabel; Tulipani, Sara; Corella, Dolores; Estruch, Ramon; Tinahones, Francisco J; Andres-Lacueva, Cristina

    2015-09-01

    The discovery of biomarkers of intake in nutritional epidemiological studies is essential in establishing an association between dietary intake (considering their bioavailability) and diet-related risk factors for diseases. The aim is to study urine and plasma phenolic and microbial profile by targeted metabolomics approach in a wine intervention clinical trial for discovering and evaluating food intake biomarkers. High-risk male volunteers (n = 36) were included in a randomized, crossover intervention clinical trial. After a washout period, subjects received red wine or gin, or dealcoholized red wine over four weeks. Fasting plasma and 24-h urine were collected at baseline and after each intervention period. A targeted metabolomic analysis of 70 host and microbial phenolic metabolites was performed using ultra performance liquid chromatography-tandem mass spectrometer (UPLC-MS/MS). Metabolites were subjected to stepwise logistic regression to establish prediction models and received operation curves were performed to evaluate biomarkers. Prediction models based mainly on gallic acid metabolites, obtained sensitivity, specificity and area under the curve (AUC) for the training and validation sets of between 91 and 98% for urine and between 74 and 91% for plasma. Resveratrol, ethylgallate and gallic acid metabolite groups in urine samples also resulted in being good predictors of wine intake (AUC>87%). However, lower values for metabolites were obtained in plasma samples. The highest correlations between fasting plasma and urine were obtained for the prediction model score (r = 0.6, P<0.001), followed by gallic acid metabolites (r = 0.5-0.6, P<0.001). This study provides new insights into the discovery of food biomarkers in different biological samples. © 2015 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Heyman, Heino M.; Zhang, Xing; Tang, Keqi

    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.

  12. Assessment of Genetically Modified Soybean in Relation to Natural Variation in the Soybean Seed Metabolome

    PubMed Central

    Clarke, Joseph D.; Alexander, Danny C.; Ward, Dennis P.; Ryals, John A.; Mitchell, Matthew W.; Wulff, Jacob E.; Guo, Lining

    2013-01-01

    Genetically modified (GM) crops currently constitute a significant and growing part of agriculture. An important aspect of GM crop adoption is to demonstrate safety and equivalence with respect to conventional crops. Untargeted metabolomics has the ability to profile diverse classes of metabolites and thus could be an adjunct for GM crop substantial equivalence assessment. To account for environmental effects and introgression of GM traits into diverse genetic backgrounds, we propose that the assessment for GM crop metabolic composition should be understood within the context of the natural variation for the crop. Using a non-targeted metabolomics platform, we profiled 169 metabolites and established their dynamic ranges from the seeds of 49 conventional soybean lines representing the current commercial genetic diversity. We further demonstrated that the metabolome of a GM line had no significant deviation from natural variation within the soybean metabolome, with the exception of changes in the targeted engineered pathway. PMID:24170158

  13. Non-targeted Metabolomics in Diverse Sorghum Breeding Lines Indicates Primary and Secondary Metabolite Profiles Are Associated with Plant Biomass Accumulation and Photosynthesis

    DOE PAGES

    Turner, Marie F.; Heuberger, Adam L.; Kirkwood, Jay S.; ...

    2016-07-11

    Metabolomics is an emerging method to improve our understanding of how genetic diversity affects phenotypic variation in plants. Recent studies have demonstrated that genotype has a major influence on biochemical variation in several types of plant tissues, however, the association between metabolic variation and variation in morphological and physiological traits is largely unknown. Sorghum bicolor (L.) is an important food and fuel crop with extensive genetic and phenotypic variation. Sorghum lines have been bred for differing phenotypes beneficial for production of grain (food), stem sugar (food, fuel), and cellulosic biomass (forage, fuel), and these varying phenotypes are the end productsmore » of innate metabolic programming which determines how carbon is allocated during plant growth and development. Further, sorghum has been adapted among highly diverse environments. Because of this geographic and phenotypic variation, the sorghum metabolome is expected to be highly divergent; however, metabolite variation in sorghum has not been characterized. Here, we utilize a phenotypically diverse panel of sorghum breeding lines to identify associations between leaf metabolites and morpho-physiological traits. The panel (11 lines) exhibited significant variation for 21 morpho-physiological traits, as well as broader trends in variation by sorghum type (grain vs. biomass types). Variation was also observed for cell wall constituents (glucan, xylan, lignin, ash). Non-targeted metabolomics analysis of leaf tissue showed that 956 of 1181 metabolites varied among the lines (81%, ANOVA, FDR adjusted p < 0.05). Both univariate and multivariate analyses determined relationships between metabolites and morpho-physiological traits, and 384 metabolites correlated with at least one trait (32%, p < 0.05), including many secondary metabolites such as glycosylated flavonoids and chlorogenic acids. The use of metabolomics to explain relationships between two or more morpho

  14. Non-targeted Metabolomics in Diverse Sorghum Breeding Lines Indicates Primary and Secondary Metabolite Profiles Are Associated with Plant Biomass Accumulation and Photosynthesis

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Turner, Marie F.; Heuberger, Adam L.; Kirkwood, Jay S.

    Metabolomics is an emerging method to improve our understanding of how genetic diversity affects phenotypic variation in plants. Recent studies have demonstrated that genotype has a major influence on biochemical variation in several types of plant tissues, however, the association between metabolic variation and variation in morphological and physiological traits is largely unknown. Sorghum bicolor (L.) is an important food and fuel crop with extensive genetic and phenotypic variation. Sorghum lines have been bred for differing phenotypes beneficial for production of grain (food), stem sugar (food, fuel), and cellulosic biomass (forage, fuel), and these varying phenotypes are the end productsmore » of innate metabolic programming which determines how carbon is allocated during plant growth and development. Further, sorghum has been adapted among highly diverse environments. Because of this geographic and phenotypic variation, the sorghum metabolome is expected to be highly divergent; however, metabolite variation in sorghum has not been characterized. Here, we utilize a phenotypically diverse panel of sorghum breeding lines to identify associations between leaf metabolites and morpho-physiological traits. The panel (11 lines) exhibited significant variation for 21 morpho-physiological traits, as well as broader trends in variation by sorghum type (grain vs. biomass types). Variation was also observed for cell wall constituents (glucan, xylan, lignin, ash). Non-targeted metabolomics analysis of leaf tissue showed that 956 of 1181 metabolites varied among the lines (81%, ANOVA, FDR adjusted p < 0.05). Both univariate and multivariate analyses determined relationships between metabolites and morpho-physiological traits, and 384 metabolites correlated with at least one trait (32%, p < 0.05), including many secondary metabolites such as glycosylated flavonoids and chlorogenic acids. The use of metabolomics to explain relationships between two or more morpho

  15. Metabolomics in chemical ecology.

    PubMed

    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.

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

    PubMed

    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".

  17. Identification and Quantitation of Malonic Acid Biomarkers of In-Born Error Metabolism by Targeted Metabolomics

    NASA Astrophysics Data System (ADS)

    Ambati, Chandra Shekar R.; Yuan, Furong; Abu-Elheiga, Lutfi A.; Zhang, Yiqing; Shetty, Vivekananda

    2017-05-01

    Malonic acid (MA), methylmalonic acid (MMA), and ethylmalonic acid (EMA) metabolites are implicated in various non-cancer disorders that are associated with inborn-error metabolism. In this study, we have slightly modified the published 3-nitrophenylhydrazine (3NPH) derivatization method and applied it to derivatize MA, MMA, and EMA to their hydrazone derivatives, which were amenable for liquid chromatography- mass spectrometry (LC-MS) quantitation. 3NPH was used to derivatize MA, MMA, and EMA, and multiple reaction monitoring (MRM) transitions of the corresponding derivatives were determined by product-ion experiments. Data normalization and absolute quantitation were achieved by using 3NPH derivatized isotopic labeled compounds 13C2-MA, MMA-D3, and EMA-D3. The detection limits were found to be at nanomolar concentrations and a good linearity was achieved from nanomolar to millimolar concentrations. As a proof of concept study, we have investigated the levels of malonic acids in mouse plasma with malonyl-CoA decarboxylase deficiency (MCD-D), and we have successfully applied 3NPH method to identify and quantitate all three malonic acids in wild type (WT) and MCD-D plasma with high accuracy. The results of this method were compared with that of underivatized malonic acid standards experiments that were performed using hydrophilic interaction liquid chromatography (HILIC)-MRM. Compared with HILIC method, 3NPH derivatization strategy was found to be very efficient to identify these molecules as it greatly improved the sensitivity, quantitation accuracy, as well as peak shape and resolution. Furthermore, there was no matrix effect in LC-MS analysis and the derivatized metabolites were found to be very stable for longer time.

  18. Quantitative proteomics in cardiovascular research: global and targeted strategies

    PubMed Central

    Shen, Xiaomeng; Young, Rebeccah; Canty, John M.; Qu, Jun

    2014-01-01

    Extensive technical advances in the past decade have substantially expanded quantitative proteomics in cardiovascular research. This has great promise for elucidating the mechanisms of cardiovascular diseases (CVD) and the discovery of cardiac biomarkers used for diagnosis and treatment evaluation. Global and targeted proteomics are the two major avenues of quantitative proteomics. While global approaches enable unbiased discovery of altered proteins via relative quantification at the proteome level, targeted techniques provide higher sensitivity and accuracy, and are capable of multiplexed absolute quantification in numerous clinical/biological samples. While promising, technical challenges need to be overcome to enable full utilization of these techniques in cardiovascular medicine. Here we discuss recent advances in quantitative proteomics and summarize applications in cardiovascular research with an emphasis on biomarker discovery and elucidating molecular mechanisms of disease. We propose the integration of global and targeted strategies as a high-throughput pipeline for cardiovascular proteomics. Targeted approaches enable rapid, extensive validation of biomarker candidates discovered by global proteomics. These approaches provide a promising alternative to immunoassays and other low-throughput means currently used for limited validation. PMID:24920501

  19. Development of high-performance chemical isotope labeling LC-MS for profiling the human fecal metabolome.

    PubMed

    Xu, Wei; Chen, Deying; Wang, Nan; Zhang, Ting; Zhou, Ruokun; Huan, Tao; Lu, Yingfeng; Su, Xiaoling; Xie, Qing; Li, Liang; Li, Lanjuan

    2015-01-20

    Human fecal samples contain endogenous human metabolites, gut microbiota metabolites, and other compounds. Profiling the fecal metabolome can produce metabolic information that may be used not only for disease biomarker discovery, but also for providing an insight about the relationship of the gut microbiome and human health. In this work, we report a chemical isotope labeling liquid chromatography-mass spectrometry (LC-MS) method for comprehensive and quantitative analysis of the amine- and phenol-containing metabolites in fecal samples. Differential (13)C2/(12)C2-dansyl labeling of the amines and phenols was used to improve LC separation efficiency and MS detection sensitivity. Water, methanol, and acetonitrile were examined as an extraction solvent, and a sequential water-acetonitrile extraction method was found to be optimal. A step-gradient LC-UV setup and a fast LC-MS method were evaluated for measuring the total concentration of dansyl labeled metabolites that could be used for normalizing the sample amounts of individual samples for quantitative metabolomics. Knowing the total concentration was also useful for optimizing the sample injection amount into LC-MS to maximize the number of metabolites detectable while avoiding sample overloading. For the first time, dansylation isotope labeling LC-MS was performed in a simple time-of-flight mass spectrometer, instead of high-end equipment, demonstrating the feasibility of using a low-cost instrument for chemical isotope labeling metabolomics. The developed method was applied for profiling the amine/phenol submetabolome of fecal samples collected from three families. An average of 1785 peak pairs or putative metabolites were found from a 30 min LC-MS run. From 243 LC-MS runs of all the fecal samples, a total of 6200 peak pairs were detected. Among them, 67 could be positively identified based on the mass and retention time match to a dansyl standard library, while 581 and 3197 peak pairs could be putatively

  20. Metabolomics of Early Stage Plant Cell–Microbe Interaction Using Stable Isotope Labeling

    PubMed Central

    Pang, Qiuying; Zhang, Tong; Wang, Yang; Kong, Wenwen; Guan, Qijie; Yan, Xiufeng; Chen, Sixue

    2018-01-01

    Metabolomics has been used in unraveling metabolites that play essential roles in plant–microbe (including pathogen) interactions. However, the problem of profiling a plant metabolome with potential contaminating metabolites from the coexisting microbes has been largely ignored. To address this problem, we implemented an effective stable isotope labeling approach, where the metabolome of a plant bacterial pathogen Pseudomonas syringae pv. tomato (Pst) DC3000 was labeled with heavy isotopes. The labeled bacterial cells were incubated with Arabidopsis thaliana epidermal peels (EPs) with guard cells, and excessive bacterial cells were subsequently removed from the plant tissues by washing. The plant metabolites were characterized by liquid chromatography mass spectrometry using multiple reactions monitoring, which can differentiate plant and bacterial metabolites. Targeted metabolomic analysis suggested that Pst DC3000 infection may modulate stomatal movement by reprograming plant signaling and primary metabolic pathways. This proof-of-concept study demonstrates the utility of this strategy in differentiation of the plant and microbe metabolomes, and it has broad applications in studying metabolic interactions between microbes and other organisms. PMID:29922325

  1. Differential Off-line LC-NMR (DOLC-NMR) Metabolomics To Monitor Tyrosine-Induced Metabolome Alterations in Saccharomyces cerevisiae.

    PubMed

    Hammerl, Richard; Frank, Oliver; Hofmann, Thomas

    2017-04-19

    A novel differential off-line LC-NMR approach (DOLC-NMR) was developed to capture and quantify nutrient-induced metabolome alterations in Saccharomyces cerevisiae. Off-line coupling of HPLC separation and 1 H NMR spectroscopy supported by automated comparative bucket analyses, followed by quantitative 1 H NMR using ERETIC 2 (electronic reference to access in vivo concentrations), has been successfully used to quantitatively record changes in the metabolome of S. cerevisiae upon intervention with the aromatic amino acid l-tyrosine. Among the 33 metabolites identified, glyceryl succinate, tyrosol acetate, tyrosol lactate, tyrosol succinate, and N-acyl-tyrosine derivatives such as N-(1-oxooctyl)-tyrosine are reported for the first time as yeast metabolites. Depending on the chain length, N-(1-oxooctyl)-, N-(1-oxodecanyl)-, N-(1-oxododecanyl)-, N-(1-oxomyristinyl)-, N-(1-oxopalmityl)-, and N-(1-oxooleoyl)-l-tyrosine imparted a kokumi taste enhancement above their recognition thresholds ranging between 145 and 1432 μmol/L (model broth). Finally, carbon module labeling (CAMOLA) and carbon bond labeling (CABOLA) experiments with 13 C 6 -glucose as the carbon source confirmed the biosynthetic pathway leading to the key metabolites; for example, the aliphatic side chain of N-(1-oxooctyl)-tyrosine could be shown to be generated via de novo fatty acid biosynthesis from four C 2 -carbon modules (acetyl-CoA) originating from glucose.

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

    PubMed

    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

  3. Evaluation of intensity drift correction strategies using MetaboDrift, a normalization tool for multi-batch metabolomics data.

    PubMed

    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

  4. Phase calibration target for quantitative phase imaging with ptychography.

    PubMed

    Godden, T M; Muñiz-Piniella, A; Claverley, J D; Yacoot, A; Humphry, M J

    2016-04-04

    Quantitative phase imaging (QPI) utilizes refractive index and thickness variations that lead to optical phase shifts. This gives contrast to images of transparent objects. In quantitative biology, phase images are used to accurately segment cells and calculate properties such as dry mass, volume and proliferation rate. The fidelity of the measured phase shifts is of critical importance in this field. However to date, there has been no standardized method for characterizing the performance of phase imaging systems. Consequently, there is an increasing need for protocols to test the performance of phase imaging systems using well-defined phase calibration and resolution targets. In this work, we present a candidate for a standardized phase resolution target, and measurement protocol for the determination of the transfer of spatial frequencies, and sensitivity of a phase imaging system. The target has been carefully designed to contain well-defined depth variations over a broadband range of spatial frequencies. In order to demonstrate the utility of the target, we measure quantitative phase images on a ptychographic microscope, and compare the measured optical phase shifts with Atomic Force Microscopy (AFM) topography maps and surface profile measurements from coherence scanning interferometry. The results show that ptychography has fully quantitative nanometer sensitivity in optical path differences over a broadband range of spatial frequencies for feature sizes ranging from micrometers to hundreds of micrometers.

  5. METABOLOMICS IN SMALL FISH TOXICOLOGY AND ECOLOGICAL RISK ASSESSMENTS

    EPA Science Inventory

    The US EPA is tasked with protecting not only humans, but also ecosystems from potentially harmful effects of chemical pollutants. Although lagging behind applications targeted to human endpoints, metabolomics offers great potential in ecotoxicology. Indeed, the advantages of met...

  6. Metabolomics and Epidemiology Working Group

    Cancer.gov

    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.

  7. Development of isotope labeling LC-MS for human salivary metabolomics and application to profiling metabolome changes associated with mild cognitive impairment.

    PubMed

    Zheng, Jiamin; Dixon, Roger A; Li, Liang

    2012-12-18

    Saliva is a readily available biofluid that may contain metabolites of interest for diagnosis and prognosis of diseases. In this work, a differential (13)C/(12)C isotope dansylation labeling method, combined with liquid chromatography Fourier transform ion cyclotron resonance mass spectrometry (LC-FTICR-MS), is described for quantitative profiling of the human salivary metabolome. New strategies are presented to optimize the sample preparation and LC-MS detection processes. The strategies allow the use of as little of 5 μL of saliva sample as a starting material to determine the concentration changes of an average of 1058 ion pairs or putative metabolites in comparative saliva samples. The overall workflow consists of several steps including acetone-induced protein precipitation, (12)C-dansylation labeling of the metabolites, and LC-UV measurement of the total concentration of the labeled metabolites in individual saliva samples. A pooled sample was prepared from all the individual samples and labeled with (13)C-dansylation to serve as a reference. Using this metabolome profiling method, it was found that compatible metabolome results could be obtained after saliva samples were stored in tubes normally used for genetic material collection at room temperature, -20 °C freezer, and -80 °C freezer over a period of 1 month, suggesting that many saliva samples already collected in genomic studies could become a valuable resource for metabolomics studies, although the effect of much longer term of storage remains to be determined. Finally, the developed method was applied for analyzing the metabolome changes of two different groups: normal healthy older adults and comparable older adults with mild cognitive impairment (MCI). Top-ranked 18 metabolites successfully distinguished the two groups, among which seven metabolites were putatively identified while one metabolite, taurine, was definitively identified.

  8. Metabolomics analysis identifies sex-associated metabotypes of oxidative stress and the autotaxin–lysoPA axis in COPD

    PubMed Central

    Naz, Shama; Kolmert, Johan; Yang, Mingxing; Reinke, Stacey N.; Kamleh, Muhammad Anas; Snowden, Stuart; Heyder, Tina; Levänen, Bettina; Erle, David J.; Sköld, C. Magnus; Wheelock, Åsa M.; Wheelock, Craig E.

    2017-01-01

    Chronic obstructive pulmonary disease (COPD) is a heterogeneous disease and a leading cause of mortality and morbidity worldwide. The aim of this study was to investigate the sex dependency of circulating metabolic profiles in COPD. Serum from healthy never-smokers (healthy), smokers with normal lung function (smokers), and smokers with COPD (COPD; Global Initiative for Chronic Obstructive Lung Disease stages I–II/A–B) from the Karolinska COSMIC cohort (n=116) was analysed using our nontargeted liquid chromatography–high resolution mass spectrometry metabolomics platform. Pathway analyses revealed that several altered metabolites are involved in oxidative stress. Supervised multivariate modelling showed significant classification of smokers from COPD (p=2.8×10−7). Sex stratification indicated that the separation was driven by females (p=2.4×10−7) relative to males (p=4.0×10−4). Significantly altered metabolites were confirmed quantitatively using targeted metabolomics. Multivariate modelling of targeted metabolomics data confirmed enhanced metabolic dysregulation in females with COPD (p=3.0×10−3) relative to males (p=0.10). The autotaxin products lysoPA (16:0) and lysoPA (18:2) correlated with lung function (forced expiratory volume in 1 s) in males with COPD (r=0.86; p<0.0001), but not females (r=0.44; p=0.15), potentially related to observed dysregulation of the miR-29 family in the lung. These findings highlight the role of oxidative stress in COPD, and suggest that sex-enhanced dysregulation in oxidative stress, and potentially the autotaxin–lysoPA axis, are associated with disease mechanisms and/or prevalence. PMID:28642310

  9. Siderophore biosynthesis coordinately modulated the virulence-associated interactive metabolome of uropathogenic Escherichia coli and human urine.

    PubMed

    Su, Qiao; Guan, Tianbing; Lv, Haitao

    2016-04-14

    Uropathogenic Escherichia coli (UPEC) growth in women's bladders during urinary tract infection (UTI) incurs substantial chemical exchange, termed the "interactive metabolome", which primarily accounts for the metabolic costs (utilized metabolome) and metabolic donations (excreted metabolome) between UPEC and human urine. Here, we attempted to identify the individualized interactive metabolome between UPEC and human urine. We were able to distinguish UPEC from non-UPEC by employing a combination of metabolomics and genetics. Our results revealed that the interactive metabolome between UPEC and human urine was markedly different from that between non-UPEC and human urine, and that UPEC triggered much stronger perturbations in the interactive metabolome in human urine. Furthermore, siderophore biosynthesis coordinately modulated the individualized interactive metabolome, which we found to be a critical component of UPEC virulence. The individualized virulence-associated interactive metabolome contained 31 different metabolites and 17 central metabolic pathways that were annotated to host these different metabolites, including energetic metabolism, amino acid metabolism, and gut microbe metabolism. Changes in the activities of these pathways mechanistically pinpointed the virulent capability of siderophore biosynthesis. Together, our findings provide novel insights into UPEC virulence, and we propose that siderophores are potential targets for further discovery of drugs to treat UPEC-induced UTI.

  10. Metabolomics: the apogee of the omic triology

    PubMed Central

    Patti, Gary J; Yanes, Oscar; Siuzdak, Gary

    2013-01-01

    Metabolites, the chemical entities that are transformed during metabolism, provide a functional readout of cellular biochemistry. With emerging technologies in mass spectrometry, thousands of metabolites can now be quantitatively measured from minimal amounts of biological material, which has thereby enabled systems-level analyses. By performing global metabolite profiling, also known as untargeted metabolomics, new discoveries linking cellular pathways to biological mechanism are being revealed and shaping our understanding of cell biology, physiology, and medicine. PMID:22436749

  11. Customized Consensus Spectral Library Building for Untargeted Quantitative Metabolomics Analysis with Data Independent Acquisition Mass Spectrometry and MetaboDIA Workflow.

    PubMed

    Chen, Gengbo; Walmsley, Scott; Cheung, Gemmy C M; Chen, Liyan; Cheng, Ching-Yu; Beuerman, Roger W; Wong, Tien Yin; Zhou, Lei; Choi, Hyungwon

    2017-05-02

    Data independent acquisition-mass spectrometry (DIA-MS) coupled with liquid chromatography is a promising approach for rapid, automatic sampling of MS/MS data in untargeted metabolomics. However, wide isolation windows in DIA-MS generate MS/MS spectra containing a mixed population of fragment ions together with their precursor ions. This precursor-fragment ion map in a comprehensive MS/MS spectral library is crucial for relative quantification of fragment ions uniquely representative of each precursor ion. However, existing reference libraries are not sufficient for this purpose since the fragmentation patterns of small molecules can vary in different instrument setups. Here we developed a bioinformatics workflow called MetaboDIA to build customized MS/MS spectral libraries using a user's own data dependent acquisition (DDA) data and to perform MS/MS-based quantification with DIA data, thus complementing conventional MS1-based quantification. MetaboDIA also allows users to build a spectral library directly from DIA data in studies of a large sample size. Using a marine algae data set, we show that quantification of fragment ions extracted with a customized MS/MS library can provide as reliable quantitative data as the direct quantification of precursor ions based on MS1 data. To test its applicability in complex samples, we applied MetaboDIA to a clinical serum metabolomics data set, where we built a DDA-based spectral library containing consensus spectra for 1829 compounds. We performed fragment ion quantification using DIA data using this library, yielding sensitive differential expression analysis.

  12. Metabolomic Analysis in Brain Research: Opportunities and Challenges

    PubMed Central

    Vasilopoulou, Catherine G.; Margarity, Marigoula; Klapa, Maria I.

    2016-01-01

    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. PMID:27252656

  13. Quantitative Metabolomic Analysis of Urinary Citrulline and Calcitroic Acid in Mice after Exposure to Various Types of Ionizing Radiation.

    PubMed

    Goudarzi, Maryam; Chauthe, Siddheshwar; Strawn, Steven J; Weber, Waylon M; Brenner, David J; Fornace, Albert J

    2016-05-20

    With the safety of existing nuclear power plants being brought into question after the Fukushima disaster and the increased level of concern over terrorism-sponsored use of improvised nuclear devices, it is more crucial to develop well-defined radiation injury markers in easily accessible biofluids to help emergency-responders with injury assessment during patient triage. Here, we focused on utilizing ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) to identify and quantitate the unique changes in the urinary excretion of two metabolite markers, calcitroic acid and citrulline, in mice induced by different forms of irradiation; external γ irradiation at a low dose rate (LDR) of 3.0 mGy/min and a high dose rate (HDR) of 1.1 Gy/min, and internal exposure to Cesium-137 ((137)Cs) and Strontium-90 ((90)Sr). The multiple reaction monitoring analysis showed that, while exposure to (137)Cs and (90)Sr induced a statistically significant and persistent decrease, similar doses of external γ beam at the HDR had the opposite effect, and the LDR had no effect on the urinary levels of these two metabolites. This suggests that the source of exposure and the dose rate strongly modulate the in vivo metabolomic injury responses, which may have utility in clinical biodosimetry assays for the assessment of exposure in an affected population. This study complements our previous investigations into the metabolomic profile of urine from mice internally exposed to (90)Sr and (137)Cs and to external γ beam radiation.

  14. Quantitative Metabolomic Analysis of Urinary Citrulline and Calcitroic Acid in Mice after Exposure to Various Types of Ionizing Radiation

    PubMed Central

    Goudarzi, Maryam; Chauthe, Siddheshwar; Strawn, Steven J.; Weber, Waylon M.; Brenner, David J.; Fornace, Albert J.

    2016-01-01

    With the safety of existing nuclear power plants being brought into question after the Fukushima disaster and the increased level of concern over terrorism-sponsored use of improvised nuclear devices, it is more crucial to develop well-defined radiation injury markers in easily accessible biofluids to help emergency-responders with injury assessment during patient triage. Here, we focused on utilizing ultra performance liquid chromatography-tandem mass spectrometry (UPLC-MS/MS) to identify and quantitate the unique changes in the urinary excretion of two metabolite markers, calcitroic acid and citrulline, in mice induced by different forms of irradiation; X-ray irradiation at a low dose rate (LDR) of 3.0 mGy/min and a high dose rate (HDR) of 1.1 Gy/min, and internal exposure to Cesium-137 (137Cs) and Strontium-90 (90Sr). The multiple reaction monitoring analysis showed that, while exposure to 137Cs and 90Sr induced a statistically significant and persistent decrease, similar doses of X-ray beam at the HDR had the opposite effect, and the LDR had no effect on the urinary levels of these two metabolites. This suggests that the source of exposure and the dose rate strongly modulate the in vivo metabolomic injury responses, which may have utility in clinical biodosimetry assays for the assessment of exposure in an affected population. This study complements our previous investigations into the metabolomic profile of urine from mice internally exposed to 90Sr and 137Cs and to X-ray beam radiation. PMID:27213362

  15. Chemical Isotope Labeling LC-MS for High Coverage and Quantitative Profiling of the Hydroxyl Submetabolome in Metabolomics.

    PubMed

    Zhao, Shuang; Luo, Xian; Li, Liang

    2016-11-01

    A key step in metabolomics is to perform accurate relative quantification of the metabolomes in comparative samples with high coverage. Hydroxyl-containing metabolites are an important class of the metabolome with diverse structures and physical/chemical properties; however, many of them are difficult to detect with high sensitivity. We present a high-performance chemical isotope labeling liquid chromatography mass spectrometry (LC-MS) technique for in-depth profiling of the hydroxyl submetabolome, which involves the use of acidic liquid-liquid extraction to enrich hydroxyl metabolites into ethyl acetate from an aqueous sample. After drying and then redissolving in acetonitrile, the metabolite extract is labeled using a base-activated 12 C- or 13 C-dansylation reaction. A fast step-gradient LC-UV method is used to determine the total concentration of labeled metabolites. On the basis of the concentration information, a 12 C-labeled individual sample is mixed with an equal mole amount of a 13 C-labeled pool or control for relative metabolite quantification. The 12 C-/ 13 C-labeled mixtures are individually analyzed by LC-MS, and the resultant peak pairs of labeled metabolites in MS are measured for relative quantification and metabolite identification. A standard library of 85 hydroxyl compounds containing MS, retention time, and MS/MS information was constructed for positive metabolite identification based on matches of two or all three of these parameters with those of an unknown. Using human urine as an example, we analyzed samples of 1:1 12 C-/ 13 C-labeled urine in triplicate with triplicate runs per sample and detected an average of 3759 ± 45 peak pairs or metabolites per run and 3538 ± 71 pairs per sample with 3093 pairs in common (n = 9). Out of the 3093 peak pairs, 2304 pairs (75%) could be positively or putatively identified based on metabolome database searches, including 20 pairs positively identified using the dansylated hydroxyl standards library

  16. Metabolomic Studies in Drosophila.

    PubMed

    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.

  17. Best-Matched Internal Standard Normalization in Liquid Chromatography-Mass Spectrometry Metabolomics Applied to Environmental Samples.

    PubMed

    Boysen, Angela K; Heal, Katherine R; Carlson, Laura T; Ingalls, Anitra E

    2018-01-16

    The goal of metabolomics is to measure the entire range of small organic molecules in biological samples. In liquid chromatography-mass spectrometry-based metabolomics, formidable analytical challenges remain in removing the nonbiological factors that affect chromatographic peak areas. These factors include sample matrix-induced ion suppression, chromatographic quality, and analytical drift. The combination of these factors is referred to as obscuring variation. Some metabolomics samples can exhibit intense obscuring variation due to matrix-induced ion suppression, rendering large amounts of data unreliable and difficult to interpret. Existing normalization techniques have limited applicability to these sample types. Here we present a data normalization method to minimize the effects of obscuring variation. We normalize peak areas using a batch-specific normalization process, which matches measured metabolites with isotope-labeled internal standards that behave similarly during the analysis. This method, called best-matched internal standard (B-MIS) normalization, can be applied to targeted or untargeted metabolomics data sets and yields relative concentrations. We evaluate and demonstrate the utility of B-MIS normalization using marine environmental samples and laboratory grown cultures of phytoplankton. In untargeted analyses, B-MIS normalization allowed for inclusion of mass features in downstream analyses that would have been considered unreliable without normalization due to obscuring variation. B-MIS normalization for targeted or untargeted metabolomics is freely available at https://github.com/IngallsLabUW/B-MIS-normalization .

  18. METABOLOMICS AS A DIAGNOSTIC TOOL FOR SMALL FISH TOXICOLOGY RESEARCH

    EPA Science Inventory

    Metabolomics involves the application of advanced analytical and statistical tools to profile changes in levels of endogenous metabolites in tissues and biofluids resulting from disease onset or stress. While certain metabolites are being specifically targeted in these studies, w...

  19. The future of metabolomics in ELIXIR

    PubMed Central

    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

  20. The future of metabolomics in ELIXIR.

    PubMed

    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.

  1. Validation of metabolomics analysis of human perilymph fluid using liquid chromatography-mass spectroscopy.

    PubMed

    Mavel, Sylvie; Lefèvre, Antoine; Bakhos, David; Dufour-Rainfray, Diane; Blasco, Hélène; Emond, Patrick

    2018-05-22

    Although there is some data from animal studies, the metabolome of inner ear fluid in humans remains unknown. Characterization of the metabolome of the perilymph would allow for better understanding of its role in auditory function and for identification of biomarkers that might allow prediction of response to therapeutics. There is a major technical challenge due to the small sample of perilymph fluid available for analysis (sub-microliter). The objectives of this study were to develop and validate a methodology for analysis of perilymph metabolome using liquid chromatography-high resolution mass spectrometry (LC-HRMS). Due to the low availability of perilymph fluid; a methodological study was first performed using low volumes (0.8 μL) of cerebrospinal fluid (CSF) and optimized the LC-HRMS parameters using targeted and non-targeted metabolomics approaches. We obtained excellent parameters of reproducibility for about 100 metabolites. This methodology was then used to analyze perilymph fluid using two complementary chromatographic supports: reverse phase (RP-C18) and hydrophilic interaction liquid chromatography (HILIC). Both methods were highly robust and showed their complementarity, thus reinforcing the interest to combine these chromatographic supports. A fingerprinting was obtained from 98 robust metabolites (analytical variability <30%), where amino acids (e.g., asparagine, valine, glutamine, alanine, etc.), carboxylic acids and derivatives (e.g., lactate, carnitine, trigonelline, creatinine, etc.) were observed as first-order signals. This work lays the foundations of a robust analytical workflow for the exploration of the perilymph metabolome dedicated to the research of biomarkers for the diagnosis/prognosis of auditory pathologies. Copyright © 2018 Elsevier B.V. All rights reserved.

  2. Siderophore biosynthesis coordinately modulated the virulence-associated interactive metabolome of uropathogenic Escherichia coli and human urine

    PubMed Central

    Su, Qiao; Guan, Tianbing; Lv, Haitao

    2016-01-01

    Uropathogenic Escherichia coli (UPEC) growth in women’s bladders during urinary tract infection (UTI) incurs substantial chemical exchange, termed the “interactive metabolome”, which primarily accounts for the metabolic costs (utilized metabolome) and metabolic donations (excreted metabolome) between UPEC and human urine. Here, we attempted to identify the individualized interactive metabolome between UPEC and human urine. We were able to distinguish UPEC from non-UPEC by employing a combination of metabolomics and genetics. Our results revealed that the interactive metabolome between UPEC and human urine was markedly different from that between non-UPEC and human urine, and that UPEC triggered much stronger perturbations in the interactive metabolome in human urine. Furthermore, siderophore biosynthesis coordinately modulated the individualized interactive metabolome, which we found to be a critical component of UPEC virulence. The individualized virulence-associated interactive metabolome contained 31 different metabolites and 17 central metabolic pathways that were annotated to host these different metabolites, including energetic metabolism, amino acid metabolism, and gut microbe metabolism. Changes in the activities of these pathways mechanistically pinpointed the virulent capability of siderophore biosynthesis. Together, our findings provide novel insights into UPEC virulence, and we propose that siderophores are potential targets for further discovery of drugs to treat UPEC-induced UTI. PMID:27076285

  3. Review of sample preparation strategies for MS-based metabolomic studies in industrial biotechnology.

    PubMed

    Causon, Tim J; Hann, Stephan

    2016-09-28

    Fermentation and cell culture biotechnology in the form of so-called "cell factories" now play an increasingly significant role in production of both large (e.g. proteins, biopharmaceuticals) and small organic molecules for a wide variety of applications. However, associated metabolic engineering optimisation processes relying on genetic modification of organisms used in cell factories, or alteration of production conditions remain a challenging undertaking for improving the final yield and quality of cell factory products. In addition to genomic, transcriptomic and proteomic workflows, analytical metabolomics continues to play a critical role in studying detailed aspects of critical pathways (e.g. via targeted quantification of metabolites), identification of biosynthetic intermediates, and also for phenotype differentiation and the elucidation of previously unknown pathways (e.g. via non-targeted strategies). However, the diversity of primary and secondary metabolites and the broad concentration ranges encompassed during typical biotechnological processes means that simultaneous extraction and robust analytical determination of all parts of interest of the metabolome is effectively impossible. As the integration of metabolome data with transcriptome and proteome data is an essential goal of both targeted and non-targeted methods addressing production optimisation goals, additional sample preparation steps beyond necessary sampling, quenching and extraction protocols including clean-up, analyte enrichment, and derivatisation are important considerations for some classes of metabolites, especially those present in low concentrations or exhibiting poor stability. This contribution critically assesses the potential of current sample preparation strategies applied in metabolomic studies of industrially-relevant cell factory organisms using mass spectrometry-based platforms primarily coupled to liquid-phase sample introduction (i.e. flow injection, liquid

  4. NMR methods for metabolomics of mammalian cell culture bioreactors.

    PubMed

    Aranibar, Nelly; Reily, Michael D

    2014-01-01

    Metabolomics has become an important tool for measuring pools of small molecules in mammalian cell cultures expressing therapeutic proteins. NMR spectroscopy has played an important role, largely because it requires minimal sample preparation, does not require chromatographic separation, and is quantitative. The concentrations of large numbers of small molecules in the extracellular media or within the cells themselves can be measured directly on the culture supernatant and on the supernatant of the lysed cells, respectively, and correlated with endpoints such as titer, cell viability, or glycosylation patterns. The observed changes can be used to generate hypotheses by which these parameters can be optimized. This chapter focuses on the sample preparation, data acquisition, and analysis to get the most out of NMR metabolomics data from CHO cell cultures but could easily be extended to other in vitro culture systems.

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

    PubMed

    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.

  6. FRET-based genetically-encoded sensors for quantitative monitoring of metabolites.

    PubMed

    Mohsin, Mohd; Ahmad, Altaf; Iqbal, Muhammad

    2015-10-01

    Neighboring cells in the same tissue can exist in different states of dynamic activities. After genomics, proteomics and metabolomics, fluxomics is now equally important for generating accurate quantitative information on the cellular and sub-cellular dynamics of ions and metabolite, which is critical for functional understanding of organisms. Various spectrometry techniques are used for monitoring ions and metabolites, although their temporal and spatial resolutions are limited. Discovery of the fluorescent proteins and their variants has revolutionized cell biology. Therefore, novel tools and methods targeting sub-cellular compartments need to be deployed in specific cells and targeted to sub-cellular compartments in order to quantify the target-molecule dynamics directly. We require tools that can measure cellular activities and protein dynamics with sub-cellular resolution. Biosensors based on fluorescence resonance energy transfer (FRET) are genetically encoded and hence can specifically target sub-cellular organelles by fusion to proteins or targetted sequences. Since last decade, FRET-based genetically encoded sensors for molecules involved in energy production, reactive oxygen species and secondary messengers have helped to unravel key aspects of cellular physiology. This review, describing the design and principles of sensors, presents a database of sensors for different analytes/processes, and illustrate examples of application in quantitative live cell imaging.

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

    PubMed

    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.

  8. INVESTIGATING THE ENANTIOSELECTIVE TOXICITY OF CONAZOLE FUNGICIDES IN RAINBOW TROUT THROUGH NMR BASED METABOLOMICS

    EPA Science Inventory

    Recently, metabolomics, or the quantitative measurement of a broad spectrum of metabolic responses of living systems in response to disease onset or genetic modification, has been employed to enable rapid identification of the mechanisms of toxicity for compounds of environmental...

  9. Quantitation without Calibration: Response Profile as an Indicator of Target Amount.

    PubMed

    Debnath, Mrittika; Farace, Jessica M; Johnson, Kristopher D; Nesterova, Irina V

    2018-06-21

    Quantitative assessment of biomarkers is essential in numerous contexts from decision-making in clinical situations to food quality monitoring to interpretation of life-science research findings. However, appropriate quantitation techniques are not as widely addressed as detection methods. One of the major challenges in biomarker's quantitation is the need to have a calibration for correlating a measured signal to a target amount. The step complicates the methodologies and makes them less sustainable. In this work we address the issue via a new strategy: relying on position of response profile rather than on an absolute signal value for assessment of a target's amount. In order to enable the capability we develop a target-probe binding mechanism based on a negative cooperativity effect. A proof-of-concept example demonstrates that the model is suitable for quantitative analysis of nucleic acids over a wide concentration range. The general principles of the platform will be applicable toward a variety of biomarkers such as nucleic acids, proteins, peptides, and others.

  10. Role of metabolomics in TBI research

    PubMed Central

    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

  11. Metabolomics Coupled with Proteomics Advancing Drug Discovery toward More Agile Development of Targeted Combination Therapies*

    PubMed Central

    Wang, Xijun; Zhang, Aihua; Wang, Ping; Sun, Hui; Wu, Gelin; Sun, Wenjun; Lv, Haitao; Jiao, Guozheng; Xu, Hongying; Yuan, Ye; Liu, Lian; Zou, Dixin; Wu, Zeming; Han, Ying; Yan, Guangli; Dong, Wei; Wu, Fangfang; Dong, Tianwei; Yu, Yang; Zhang, Shuxiang; Wu, Xiuhong; Tong, Xin; Meng, Xiangcai

    2013-01-01

    To enhance the therapeutic efficacy and reduce the adverse effects of traditional Chinese medicine, practitioners often prescribe combinations of plant species and/or minerals, called formulae. Unfortunately, the working mechanisms of most of these compounds are difficult to determine and thus remain unknown. In an attempt to address the benefits of formulae based on current biomedical approaches, we analyzed the components of Yinchenhao Tang, a classical formula that has been shown to be clinically effective for treating hepatic injury syndrome. The three principal components of Yinchenhao Tang are Artemisia annua L., Gardenia jasminoids Ellis, and Rheum Palmatum L., whose major active ingredients are 6,7-dimethylesculetin (D), geniposide (G), and rhein (R), respectively. To determine the mechanisms underlying the efficacy of this formula, we conducted a systematic analysis of the therapeutic effects of the DGR compound using immunohistochemistry, biochemistry, metabolomics, and proteomics. Here, we report that the DGR combination exerts a more robust therapeutic effect than any one or two of the three individual compounds by hitting multiple targets in a rat model of hepatic injury. Thus, DGR synergistically causes intensified dynamic changes in metabolic biomarkers, regulates molecular networks through target proteins, has a synergistic/additive effect, and activates both intrinsic and extrinsic pathways. PMID:23362329

  12. Metabolomics coupled with proteomics advancing drug discovery toward more agile development of targeted combination therapies.

    PubMed

    Wang, Xijun; Zhang, Aihua; Wang, Ping; Sun, Hui; Wu, Gelin; Sun, Wenjun; Lv, Haitao; Jiao, Guozheng; Xu, Hongying; Yuan, Ye; Liu, Lian; Zou, Dixin; Wu, Zeming; Han, Ying; Yan, Guangli; Dong, Wei; Wu, Fangfang; Dong, Tianwei; Yu, Yang; Zhang, Shuxiang; Wu, Xiuhong; Tong, Xin; Meng, Xiangcai

    2013-05-01

    To enhance the therapeutic efficacy and reduce the adverse effects of traditional Chinese medicine, practitioners often prescribe combinations of plant species and/or minerals, called formulae. Unfortunately, the working mechanisms of most of these compounds are difficult to determine and thus remain unknown. In an attempt to address the benefits of formulae based on current biomedical approaches, we analyzed the components of Yinchenhao Tang, a classical formula that has been shown to be clinically effective for treating hepatic injury syndrome. The three principal components of Yinchenhao Tang are Artemisia annua L., Gardenia jasminoids Ellis, and Rheum Palmatum L., whose major active ingredients are 6,7-dimethylesculetin (D), geniposide (G), and rhein (R), respectively. To determine the mechanisms underlying the efficacy of this formula, we conducted a systematic analysis of the therapeutic effects of the DGR compound using immunohistochemistry, biochemistry, metabolomics, and proteomics. Here, we report that the DGR combination exerts a more robust therapeutic effect than any one or two of the three individual compounds by hitting multiple targets in a rat model of hepatic injury. Thus, DGR synergistically causes intensified dynamic changes in metabolic biomarkers, regulates molecular networks through target proteins, has a synergistic/additive effect, and activates both intrinsic and extrinsic pathways.

  13. Plasma Metabolomics Biosignature According to HIV Stage of Infection, Pace of Disease Progression, Viremia Level and Immunological Response to Treatment.

    PubMed

    Scarpellini, Bruno; Zanoni, Michelle; Sucupira, Maria Cecilia Araripe; Truong, Hong-Ha M; Janini, Luiz Mario Ramos; Segurado, Ismael Dale Cotrin; Diaz, Ricardo Sobhie

    2016-01-01

    We evaluated plasma samples HIV-infected individuals with different phenotypic profile among five HIV-infected elite controllers and five rapid progressors after recent HIV infection and one year later and from 10 individuals subjected to antiretroviral therapy, five of whom were immunological non-responders (INR), before and after one year of antiretroviral treatment compared to 175 samples from HIV-negative patients. A targeted quantitative tandem mass spectrometry metabolomics approach was used in order to determine plasma metabolomics biosignature that may relate to HIV infection, pace of HIV disease progression, and immunological response to treatment. Twenty-five unique metabolites were identified, including five metabolites that could distinguish rapid progressors and INRs at baseline. Severe deregulation in acylcarnitine and sphingomyelin metabolism compatible with mitochondrial deficiencies was observed. β-oxidation and sphingosine-1-phosphate-phosphatase-1 activity were down-regulated, whereas acyl-alkyl-containing phosphatidylcholines and alkylglyceronephosphate synthase levels were elevated in INRs. Evidence that elite controllers harbor an inborn error of metabolism (late-onset multiple acyl-coenzyme A dehydrogenase deficiency [MADD]) was detected. Blood-based markers from metabolomics show a very high accuracy of discriminating HIV infection between varieties of controls and have the ability to predict rapid disease progression or poor antiretroviral immunological response. These metabolites can be used as biomarkers of HIV natural evolution or treatment response and provide insight into the mechanisms of the disease.

  14. Applications of Metabolomics in Cancer Studies.

    PubMed

    Armitage, Emily Grace; Ciborowski, Michal

    2017-01-01

    Since the start of metabolomics as a field of research, the number of studies related to cancer has grown to such an extent that cancer metabolomics now represents its own discipline. In this chapter, the applications of metabolomics in cancer studies are explored. Different approaches and analytical platforms can be employed for the analysis of samples depending on the goal of the study and the aspects of the cancer metabolome being investigated. Analyses have concerned a range of cancers including lung, colorectal, bladder, breast, gastric, oesophageal and thyroid, amongst others. Developments in these strategies and methodologies that have been applied are discussed, in addition to exemplifying the use of cancer metabolomics in the discovery of biomarkers and in the assessment of therapy (both pharmaceutical and nutraceutical). Finally, the application of cancer metabolomics in personalised medicine is presented.

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

    PubMed

    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.

  16. Metabolomics Analysis of Metabolic Effects of Nicotinamide Phosphoribosyltransferase (NAMPT) Inhibition on Human Cancer Cells

    PubMed Central

    Tolstikov, Vladimir; Nikolayev, Alexander; Dong, Sucai; Zhao, Genshi; Kuo, Ming-Shang

    2014-01-01

    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. PMID:25486521

  17. Sildenafil Therapy Normalizes the Aberrant Metabolomic Profile in the Comt−/− Mouse Model of Preeclampsia/Fetal Growth Restriction

    PubMed Central

    Stanley, Joanna L.; Sulek, Karolina; Andersson, Irene J.; Davidge, Sandra T.; Kenny, Louise C.; Sibley, Colin P.; Mandal, Rupasri; Wishart, David S.; Broadhurst, David I.; Baker, Philip N.

    2015-01-01

    Preeclampsia (PE) and fetal growth restriction (FGR) are serious complications of pregnancy, associated with greatly increased risk of maternal and perinatal morbidity and mortality. These complications are difficult to diagnose and no curative treatments are available. We hypothesized that the metabolomic signature of two models of disease, catechol-O-methyl transferase (COMT−/−) and endothelial nitric oxide synthase (Nos3−/−) knockout mice, would be significantly different from control C57BL/6J mice. Further, we hypothesised that any differences in COMT−/− mice would be resolved following treatment with Sildenafil, a treatment which rescues fetal growth. Targeted, quantitative comparisons of serum metabolic profiles of pregnant Nos3−/−, COMT−/− and C57BL/6J mice were made using a kit from BIOCRATES. Significant differences in 4 metabolites were observed between Nos3−/− and C57BL/6J mice (p < 0.05) and in 18 metabolites between C57BL/6J and COMT−/− mice (p < 0.05). Following treatment with Sildenafil, only 5 of the 18 previously identified differences in metabolites (p < 0.05) remained in COMT−/− mice. Metabolomic profiling of mouse models is possible, producing signatures that are clearly different from control animals. A potential new treatment, Sildenafil, is able to normalize the aberrant metabolomic profile in COMT−/− mice; as this treatment moves into clinical trials, this information may assist in assessing possible mechanisms of action. PMID:26667607

  18. [Metabolomics research of medicinal plants].

    PubMed

    Duan, Li-Xin; Dai, Yun-Tao; Sun, Chao; Chen, Shi-Lin

    2016-11-01

    Metabolomics is the comprehensively study of chemical processes involving small molecule metabolites. It is an important part of systems biology, and is widely applied in complex traditional Chinese medicine(TCM)system. Metabolites biosynthesized by medicinal plants are the effective basis for TCM. Metabolomics studies of medicinal plants will usher in a new period of vigorous development with the implementation of Herb Genome Program and the development of TCM synthetic biology. This manuscript introduces the recent research progresses of metabolomics technology and the main research contents of metabolomics studies for medicinal plants, including identification and quality evaluation for medicinal plants, cultivars breeding, stress resistance, metabolic pathways, metabolic network, metabolic engineering and synthetic biology researches. The integration of genomics, transcriptomics and metabolomics approaches will finally lay foundation for breeding of medicinal plants, R&D, quality and safety evaluation of innovative drug. Copyright© by the Chinese Pharmaceutical Association.

  19. Targeted Metabolomics Demonstrates Distinct and Overlapping Maternal Metabolites Associated With BMI, Glucose, and Insulin Sensitivity During Pregnancy Across Four Ancestry Groups.

    PubMed

    Jacob, Saya; Nodzenski, Michael; Reisetter, Anna C; Bain, James R; Muehlbauer, Michael J; Stevens, Robert D; Ilkayeva, Olga R; Lowe, Lynn P; Metzger, Boyd E; Newgard, Christopher B; Scholtens, Denise M; Lowe, William L

    2017-07-01

    We used targeted metabolomics in pregnant mothers to compare maternal metabolite associations with maternal BMI, glycemia, and insulin sensitivity. Targeted metabolomic assays of clinical metabolites, amino acids, and acylcarnitines were performed on fasting and 1-h postglucose serum samples from European ancestry, Afro-Caribbean, Thai, and Mexican American mothers (400 from each ancestry group) who participated in the Hyperglycemia and Adverse Pregnancy Outcome (HAPO) Study and underwent an oral glucose tolerance test at ∼28 weeks gestation. K-means clustering, which identified patterns of metabolite levels across ancestry groups, demonstrated that, at both fasting and 1-h, levels of the majority of metabolites were similar across ancestry groups. Meta-analyses demonstrated association of a broad array of fasting and 1-h metabolites, including lipids and amino acids and their metabolites, with maternal BMI, glucose levels, and insulin sensitivity before and after adjustment for the different phenotypes. At fasting and 1 h, a mix of metabolites was identified that were common across phenotypes or associated with only one or two phenotypes. Partial correlation estimates, which allowed comparison of the strength of association of different metabolites with maternal phenotypes, demonstrated that metabolites most strongly associated with different phenotypes included some that were common across as well as unique to each phenotype. Maternal BMI and glycemia have metabolic signatures that are both shared and unique to each phenotype. These signatures largely remain consistent across different ancestry groups and may contribute to the common and independent effects of these two phenotypes on adverse pregnancy outcomes. © 2017 by the American Diabetes Association.

  20. Targeted Metabolomics Reveals Early Dominant Optic Atrophy Signature in Optic Nerves of Opa1delTTAG/+ Mice.

    PubMed

    Chao de la Barca, Juan Manuel; Simard, Gilles; Sarzi, Emmanuelle; Chaumette, Tanguy; Rousseau, Guillaume; Chupin, Stéphanie; Gadras, Cédric; Tessier, Lydie; Ferré, Marc; Chevrollier, Arnaud; Desquiret-Dumas, Valérie; Gueguen, Naïg; Leruez, Stéphanie; Verny, Christophe; Miléa, Dan; Bonneau, Dominique; Amati-Bonneau, Patrizia; Procaccio, Vincent; Hamel, Christian; Lenaers, Guy; Reynier, Pascal; Prunier-Mirebeau, Delphine

    2017-02-01

    Dominant optic atrophy (MIM No. 165500) is a blinding condition related to mutations in OPA1, a gene encoding a large GTPase involved in mitochondrial inner membrane dynamics. Although several mouse models mimicking the disease have been developed, the pathophysiological mechanisms responsible for retinal ganglion cell degeneration remain poorly understood. Using a targeted metabolomic approach, we measured the concentrations of 188 metabolites in nine tissues, that is, brain, three types of skeletal muscle, heart, liver, retina, optic nerve, and plasma in symptomatic 11-month-old Opa1delTTAG/+ mice. Significant metabolic signatures were found only in the optic nerve and plasma of female mice. The optic nerve signature was characterized by altered concentrations of phospholipids, amino acids, acylcarnitines, and carnosine, whereas the plasma signature showed decreased concentrations of amino acids and sarcosine associated with increased concentrations of several phospholipids. In contrast, the investigation of 3-month-old presymptomatic Opa1delTTAG/+ mice showed no specific plasma signature but revealed a significant optic nerve signature in both sexes, although with a sex effect. The Opa1delTTAG/+ versus wild-type optic nerve signature was characterized by the decreased concentrations of 10 sphingomyelins and 10 lysophosphatidylcholines, suggestive of myelin sheath alteration, and by alteration in the concentrations of metabolites involved in neuroprotection, such as dimethylarginine, carnitine, spermine, spermidine, carnosine, and glutamate, suggesting a concomitant axonal metabolic dysfunction. Our comprehensive metabolomic investigations revealed in symptomatic as well as in presymptomatic Opa1delTTAG/+ mice, a specific sensitiveness of the optic nerve to Opa1 insufficiency, opening new routes for protective therapeutic strategies.

  1. Metabolomics and malaria biology

    PubMed Central

    Lakshmanan, Viswanathan; Rhee, Kyu Y.; Daily, Johanna P.

    2010-01-01

    Metabolomics has ushered in a novel and multi-disciplinary realm in biological research. It has provided researchers with a platform to combine powerful biochemical, statistical, computational, and bioinformatics techniques to delve into the mysteries of biology and disease. The application of metabolomics to study malaria parasites represents a major advance in our approach towards gaining a more comprehensive perspective on parasite biology and disease etiology. This review attempts to highlight some of the important aspects of the field of metabolomics, and its ongoing and potential future applications to malaria research. PMID:20970461

  2. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools

    PubMed Central

    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

    2016-01-01

    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. PMID:26467476

  3. Food metabolomics: from farm to human.

    PubMed

    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.

  4. Quantitative targeted proteomics for understanding the blood-brain barrier: towards pharmacoproteomics.

    PubMed

    Ohtsuki, Sumio; Hirayama, Mio; Ito, Shingo; Uchida, Yasuo; Tachikawa, Masanori; Terasaki, Tetsuya

    2014-06-01

    The blood-brain barrier (BBB) is formed by brain capillary endothelial cells linked together via complex tight junctions, and serves to prevent entry of drugs into the brain. Multiple transporters are expressed at the BBB, where they control exchange of materials between the circulating blood and brain interstitial fluid, thereby supporting and protecting the CNS. An understanding of the BBB is necessary for efficient development of CNS-acting drugs and to identify potential drug targets for treatment of CNS diseases. Quantitative targeted proteomics can provide detailed information on protein expression levels at the BBB. The present review highlights the latest applications of quantitative targeted proteomics in BBB research, specifically to evaluate species and in vivo-in vitro differences, and to reconstruct in vivo transport activity. Such a BBB quantitative proteomics approach can be considered as pharmacoproteomics.

  5. Training in metabolomics research. II. Processing and statistical analysis of metabolomics data, metabolite identification, pathway analysis, applications of metabolomics and its future

    PubMed Central

    Barnes, Stephen; Benton, H. Paul; Casazza, Krista; Cooper, Sara; Cui, Xiangqin; Du, Xiuxia; Engler, Jeffrey; Kabarowski, Janusz H.; Li, Shuzhao; Pathmasiri, Wimal; Prasain, Jeevan K.; Renfrow, Matthew B.; Tiwari, Hemant K.

    2017-01-01

    Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites, and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. This second part of a comprehensive description of the methods of metabolomics focuses on data analysis, emerging methods in metabolomics and the future of this discipline. PMID:28239968

  6. Influence of exposure to pesticide mixtures on the metabolomic profile in post-metamorphic green frogs (Lithobates clamitans)

    EPA Science Inventory

    Pesticide use in agricultural areas requires the application of numerous chemicals to control target organisms, leaving non-target organisms at risk. The present study evaluates the hepatic metabolomic profile of one group of non-target organisms, amphibians, after exposure to a ...

  7. Metabolomics Workbench: An international repository for metabolomics data and metadata, metabolite standards, protocols, tutorials and training, and analysis tools.

    PubMed

    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.

  8. Clinical Metabolomics and Glaucoma.

    PubMed

    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.

  9. MetaboLyzer: A Novel Statistical Workflow for Analyzing Post-Processed LC/MS Metabolomics Data

    PubMed Central

    Mak, Tytus D.; Laiakis, Evagelia C.; Goudarzi, Maryam; Fornace, Albert J.

    2014-01-01

    Metabolomics, the global study of small molecules in a particular system, has in the last few years risen to become a primary –omics platform for the study of metabolic processes. With the ever-increasing pool of quantitative data yielded from metabolomic research, specialized methods and tools with which to analyze and extract meaningful conclusions from these data are becoming more and more crucial. Furthermore, the depth of knowledge and expertise required to undertake a metabolomics oriented study is a daunting obstacle to investigators new to the field. As such, we have created a new statistical analysis workflow, MetaboLyzer, which aims to both simplify analysis for investigators new to metabolomics, as well as provide experienced investigators the flexibility to conduct sophisticated analysis. MetaboLyzer’s workflow is specifically tailored to the unique characteristics and idiosyncrasies of postprocessed liquid chromatography/mass spectrometry (LC/MS) based metabolomic datasets. It utilizes a wide gamut of statistical tests, procedures, and methodologies that belong to classical biostatistics, as well as several novel statistical techniques that we have developed specifically for metabolomics data. Furthermore, MetaboLyzer conducts rapid putative ion identification and putative biologically relevant analysis via incorporation of four major small molecule databases: KEGG, HMDB, Lipid Maps, and BioCyc. MetaboLyzer incorporates these aspects into a comprehensive workflow that outputs easy to understand statistically significant and potentially biologically relevant information in the form of heatmaps, volcano plots, 3D visualization plots, correlation maps, and metabolic pathway hit histograms. For demonstration purposes, a urine metabolomics data set from a previously reported radiobiology study in which samples were collected from mice exposed to gamma radiation was analyzed. MetaboLyzer was able to identify 243 statistically significant ions out of a

  10. Mechanistic and quantitative insight into cell surface targeted molecular imaging agent design.

    PubMed

    Zhang, Liang; Bhatnagar, Sumit; Deschenes, Emily; Thurber, Greg M

    2016-05-05

    Molecular imaging agent design involves simultaneously optimizing multiple probe properties. While several desired characteristics are straightforward, including high affinity and low non-specific background signal, in practice there are quantitative trade-offs between these properties. These include plasma clearance, where fast clearance lowers background signal but can reduce target uptake, and binding, where high affinity compounds sometimes suffer from lower stability or increased non-specific interactions. Further complicating probe development, many of the optimal parameters vary depending on both target tissue and imaging agent properties, making empirical approaches or previous experience difficult to translate. Here, we focus on low molecular weight compounds targeting extracellular receptors, which have some of the highest contrast values for imaging agents. We use a mechanistic approach to provide a quantitative framework for weighing trade-offs between molecules. Our results show that specific target uptake is well-described by quantitative simulations for a variety of targeting agents, whereas non-specific background signal is more difficult to predict. Two in vitro experimental methods for estimating background signal in vivo are compared - non-specific cellular uptake and plasma protein binding. Together, these data provide a quantitative method to guide probe design and focus animal work for more cost-effective and time-efficient development of molecular imaging agents.

  11. Rifaximin Modulates the Vaginal Microbiome and Metabolome in Women Affected by Bacterial Vaginosis

    PubMed Central

    Picone, Gianfranco; Cruciani, Federica; Brigidi, Patrizia; Calanni, Fiorella; Donders, Gilbert; Capozzi, Francesco; Vitali, Beatrice

    2014-01-01

    Bacterial vaginosis (BV) is a common vaginal disorder characterized by the decrease of lactobacilli and overgrowth of Gardnerella vaginalis and resident anaerobic vaginal bacteria. In the present work, the effects of rifaximin vaginal tablets on vaginal microbiota and metabolome of women affected by BV were investigated by combining quantitative PCR and a metabolomic approach based on 1H nuclear magnetic resonance. To highlight the general trends of the bacterial communities and metabolomic profiles in response to the antibiotic/placebo therapy, a multivariate statistical strategy was set up based on the trajectories traced by vaginal samples in a principal component analysis space. Our data demonstrated the efficacy of rifaximin in restoring a health-like condition in terms of both bacterial communities and metabolomic features. In particular, rifaximin treatment was significantly associated with an increase in the lactobacillus/BV-related bacteria ratio, as well as with an increase in lactic acid concentration and a decrease of a pool of metabolites typically produced by BV-related bacteria (acetic acid, succinate, short-chain fatty acids, and biogenic amines). Among the tested dosages of rifaximin (100 and 25 mg for 5 days and 100 mg for 2 days), 25 mg for 5 days was found to be the most effective. PMID:24709255

  12. A metabolomics guided exploration of marine natural product chemical space.

    PubMed

    Floros, Dimitrios J; Jensen, Paul R; Dorrestein, Pieter C; Koyama, Nobuhiro

    2016-09-01

    Natural products from culture collections have enormous impact in advancing discovery programs for metabolites of biotechnological importance. These discovery efforts rely on the metabolomic characterization of strain collections. Many emerging approaches compare metabolomic profiles of such collections, but few enable the analysis and prioritization of thousands of samples from diverse organisms while delivering chemistry specific read outs. In this work we utilize untargeted LC-MS/MS based metabolomics together with molecular networking to. This approach annotated 76 molecular families (a spectral match rate of 28 %), including clinically and biotechnologically important molecules such as valinomycin, actinomycin D, and desferrioxamine E. Targeting a molecular family produced primarily by one microorganism led to the isolation and structure elucidation of two new molecules designated maridric acids A and B. Molecular networking guided exploration of large culture collections allows for rapid dereplication of know molecules and can highlight producers of uniques metabolites. These methods, together with large culture collections and growing databases, allow for data driven strain prioritization with a focus on novel chemistries.

  13. Identification of Serum Metabolites Associated With Risk of Type 2 Diabetes Using a Targeted Metabolomic Approach

    PubMed Central

    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

    2013-01-01

    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. PMID:23043162

  14. A Metabolomic Perspective on Coeliac Disease

    PubMed Central

    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

  15. The future of liquid chromatography-mass spectrometry (LC-MS) in metabolic profiling and metabolomic studies for biomarker discovery

    PubMed Central

    Metz, Thomas O.; Zhang, Qibin; Page, Jason S.; Shen, Yufeng; Callister, Stephen J.; Jacobs, Jon M.; Smith, Richard D.

    2008-01-01

    SUMMARY The future utility of liquid chromatography-mass spectrometry (LC-MS) in metabolic profiling and metabolomic studies for biomarker discover will be discussed, beginning with a brief description of the evolution of metabolomics and the utilization of the three most popular analytical platforms in such studies: NMR, GC-MS, and LC-MS. Emphasis is placed on recent developments in high-efficiency LC separations, sensitive electrospray ionization approaches, and the benefits to incorporating both in LC-MS-based approaches. The advantages and disadvantages of various quantitative approaches are reviewed, followed by the current LC-MS-based tools available for candidate biomarker characterization and identification. Finally, a brief prediction on the future path of LC-MS-based methods in metabolic profiling and metabolomic studies is given. PMID:19177179

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

    NASA Astrophysics Data System (ADS)

    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.

  17. NAIMA: target amplification strategy allowing quantitative on-chip detection of GMOs.

    PubMed

    Morisset, Dany; Dobnik, David; Hamels, Sandrine; Zel, Jana; Gruden, Kristina

    2008-10-01

    We have developed a novel multiplex quantitative DNA-based target amplification method suitable for sensitive, specific and quantitative detection on microarray. This new method named NASBA Implemented Microarray Analysis (NAIMA) was applied to GMO detection in food and feed, but its application can be extended to all fields of biology requiring simultaneous detection of low copy number DNA targets. In a first step, the use of tailed primers allows the multiplex synthesis of template DNAs in a primer extension reaction. A second step of the procedure consists of transcription-based amplification using universal primers. The cRNA product is further on directly ligated to fluorescent dyes labelled 3DNA dendrimers allowing signal amplification and hybridized without further purification on an oligonucleotide probe-based microarray for multiplex detection. Two triplex systems have been applied to test maize samples containing several transgenic lines, and NAIMA has shown to be sensitive down to two target copies and to provide quantitative data on the transgenic contents in a range of 0.1-25%. Performances of NAIMA are comparable to singleplex quantitative real-time PCR. In addition, NAIMA amplification is faster since 20 min are sufficient to achieve full amplification.

  18. NAIMA: target amplification strategy allowing quantitative on-chip detection of GMOs

    PubMed Central

    Morisset, Dany; Dobnik, David; Hamels, Sandrine; Žel, Jana; Gruden, Kristina

    2008-01-01

    We have developed a novel multiplex quantitative DNA-based target amplification method suitable for sensitive, specific and quantitative detection on microarray. This new method named NASBA Implemented Microarray Analysis (NAIMA) was applied to GMO detection in food and feed, but its application can be extended to all fields of biology requiring simultaneous detection of low copy number DNA targets. In a first step, the use of tailed primers allows the multiplex synthesis of template DNAs in a primer extension reaction. A second step of the procedure consists of transcription-based amplification using universal primers. The cRNA product is further on directly ligated to fluorescent dyes labelled 3DNA dendrimers allowing signal amplification and hybridized without further purification on an oligonucleotide probe-based microarray for multiplex detection. Two triplex systems have been applied to test maize samples containing several transgenic lines, and NAIMA has shown to be sensitive down to two target copies and to provide quantitative data on the transgenic contents in a range of 0.1–25%. Performances of NAIMA are comparable to singleplex quantitative real-time PCR. In addition, NAIMA amplification is faster since 20 min are sufficient to achieve full amplification. PMID:18710880

  19. COnsortium of METabolomics Studies (COMETS)

    Cancer.gov

    The COnsortium of METabolomics Studies (COMETS) is an extramural-intramural partnership that promotes collaboration among prospective cohort studies that follow participants for a range of outcomes and perform metabolomic profiling of individuals.

  20. Potential Impact and Study Considerations of Metabolomics in Cardiovascular Health and Disease: A Scientific Statement From the American Heart Association.

    PubMed

    Cheng, Susan; Shah, Svati H; Corwin, Elizabeth J; Fiehn, Oliver; Fitzgerald, Robert L; Gerszten, Robert E; Illig, Thomas; Rhee, Eugene P; Srinivas, Pothur R; Wang, Thomas J; Jain, Mohit

    2017-04-01

    Through the measure of thousands of small-molecule metabolites in diverse biological systems, metabolomics now offers the potential for new insights into the factors that contribute to complex human diseases such as cardiovascular disease. Targeted metabolomics methods have already identified new molecular markers and metabolomic signatures of cardiovascular disease risk (including branched-chain amino acids, select unsaturated lipid species, and trimethylamine- N -oxide), thus in effect linking diverse exposures such as those from dietary intake and the microbiota with cardiometabolic traits. As technologies for metabolomics continue to evolve, the depth and breadth of small-molecule metabolite profiling in complex systems continue to advance rapidly, along with prospects for ongoing discovery. Current challenges facing the field of metabolomics include scaling throughput and technical capacity for metabolomics approaches, bioinformatic and chemoinformatic tools for handling large-scale metabolomics data, methods for elucidating the biochemical structure and function of novel metabolites, and strategies for determining the true clinical relevance of metabolites observed in association with cardiovascular disease outcomes. Progress made in addressing these challenges will allow metabolomics the potential to substantially affect diagnostics and therapeutics in cardiovascular medicine. © 2017 American Heart Association, Inc.

  1. Training in metabolomics research. II. Processing and statistical analysis of metabolomics data, metabolite identification, pathway analysis, applications of metabolomics and its future.

    PubMed

    Barnes, Stephen; Benton, H Paul; Casazza, Krista; Cooper, Sara J; Cui, Xiangqin; Du, Xiuxia; Engler, Jeffrey; Kabarowski, Janusz H; Li, Shuzhao; Pathmasiri, Wimal; Prasain, Jeevan K; Renfrow, Matthew B; Tiwari, Hemant K

    2016-08-01

    Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. This second part of a comprehensive description of the methods of metabolomics focuses on data analysis, emerging methods in metabolomics and the future of this discipline. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  2. Metabolomics for Biomarker Discovery in Gastroenterological Cancer

    PubMed Central

    Nishiumi, Shin; Suzuki, Makoto; Kobayashi, Takashi; Matsubara, Atsuki; Azuma, Takeshi; Yoshida, Masaru

    2014-01-01

    The study of the omics cascade, which involves comprehensive investigations based on genomics, transcriptomics, proteomics, metabolomics, etc., has developed rapidly and now plays an important role in life science research. Among such analyses, metabolome analysis, in which the concentrations of low molecular weight metabolites are comprehensively analyzed, has rapidly developed along with improvements in analytical technology, and hence, has been applied to a variety of research fields including the clinical, cell biology, and plant/food science fields. The metabolome represents the endpoint of the omics cascade and is also the closest point in the cascade to the phenotype. Moreover, it is affected by variations in not only the expression but also the enzymatic activity of several proteins. Therefore, metabolome analysis can be a useful approach for finding effective diagnostic markers and examining unknown pathological conditions. The number of studies involving metabolome analysis has recently been increasing year-on-year. Here, we describe the findings of studies that used metabolome analysis to attempt to discover biomarker candidates for gastroenterological cancer and discuss metabolome analysis-based disease diagnosis. PMID:25003943

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

    PubMed

    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.

  4. Profiling the role of mammalian target of rapamycin in the vascular smooth muscle metabolome in pulmonary arterial hypertension

    PubMed Central

    Kudryashova, Tatiana V.; Goncharov, Dmitry A.; Pena, Andressa; Ihida-Stansbury, Kaori; DeLisser, Horace; Kawut, Steven M.

    2015-01-01

    Abstract Increased proliferation and resistance to apoptosis of pulmonary arterial vascular smooth muscle cells (PAVSMCs), coupled with metabolic reprogramming, are key components of pulmonary vascular remodeling, a major and currently irreversible pathophysiological feature of pulmonary arterial hypertension (PAH). We recently reported that activation of mammalian target of rapamycin (mTOR) plays a key role in increased energy generation and maintenance of the proliferative, apoptosis-resistant PAVSMC phenotype in human PAH, but the downstream effects of mTOR activation on PAH PAVSMC metabolism are not clear. Using liquid and gas chromatography–based mass spectrometry, we performed pilot metabolomic profiling of human microvascular PAVSMCs from idiopathic-PAH subjects before and after treatment with the selective adenosine triphosphate–competitive mTOR inhibitor PP242 and from nondiseased lungs. We have shown that PAH PAVSMCs have a distinct metabolomic signature of altered metabolites—components of fatty acid synthesis, deficiency of sugars, amino sugars, and nucleotide sugars—intermediates of protein and lipid glycosylation, and downregulation of key biochemicals involved in glutathione and nicotinamide adenine dinucleotide (NAD) metabolism. We also report that mTOR inhibition attenuated or reversed the majority of the PAH-specific abnormalities in lipogenesis, glycosylation, glutathione, and NAD metabolism without affecting altered polyunsaturated fatty acid metabolism. Collectively, our data demonstrate a critical role of mTOR in major PAH PAVSMC metabolic abnormalities and suggest the existence of de novo lipid synthesis in PAVSMCs in human PAH that may represent a new, important component of disease pathogenesis worthy of future investigation. PMID:26697174

  5. Plasma Metabolomics Biosignature According to HIV Stage of Infection, Pace of Disease Progression, Viremia Level and Immunological Response to Treatment

    PubMed Central

    Scarpelini, Bruno; Zanoni, Michelle; Sucupira, Maria Cecilia Araripe; Truong, Hong-Ha M.; Janini, Luiz Mario Ramos; Segurado, Ismael Dale Cotrin; Diaz, Ricardo Sobhie

    2016-01-01

    Background We evaluated plasma samples HIV-infected individuals with different phenotypic profile among five HIV-infected elite controllers and five rapid progressors after recent HIV infection and one year later and from 10 individuals subjected to antiretroviral therapy, five of whom were immunological non-responders (INR), before and after one year of antiretroviral treatment compared to 175 samples from HIV-negative patients. A targeted quantitative tandem mass spectrometry metabolomics approach was used in order to determine plasma metabolomics biosignature that may relate to HIV infection, pace of HIV disease progression, and immunological response to treatment. Results Twenty-five unique metabolites were identified, including five metabolites that could distinguish rapid progressors and INRs at baseline. Severe deregulation in acylcarnitine and sphingomyelin metabolism compatible with mitochondrial deficiencies was observed. β-oxidation and sphingosine‐1‐phosphate-phosphatase-1 activity were down-regulated, whereas acyl-alkyl-containing phosphatidylcholines and alkylglyceronephosphate synthase levels were elevated in INRs. Evidence that elite controllers harbor an inborn error of metabolism (late-onset multiple acyl-coenzyme A dehydrogenase deficiency [MADD]) was detected. Conclusions Blood-based markers from metabolomics show a very high accuracy of discriminating HIV infection between varieties of controls and have the ability to predict rapid disease progression or poor antiretroviral immunological response. These metabolites can be used as biomarkers of HIV natural evolution or treatment response and provide insight into the mechanisms of the disease. PMID:27941971

  6. A General Method for Targeted Quantitative Cross-Linking Mass Spectrometry.

    PubMed

    Chavez, Juan D; Eng, Jimmy K; Schweppe, Devin K; Cilia, Michelle; Rivera, Keith; Zhong, Xuefei; Wu, Xia; Allen, Terrence; Khurgel, Moshe; Kumar, Akhilesh; Lampropoulos, Athanasios; Larsson, Mårten; Maity, Shuvadeep; Morozov, Yaroslav; Pathmasiri, Wimal; Perez-Neut, Mathew; Pineyro-Ruiz, Coriness; Polina, Elizabeth; Post, Stephanie; Rider, Mark; Tokmina-Roszyk, Dorota; Tyson, Katherine; Vieira Parrine Sant'Ana, Debora; Bruce, James E

    2016-01-01

    Chemical cross-linking mass spectrometry (XL-MS) provides protein structural information by identifying covalently linked proximal amino acid residues on protein surfaces. The information gained by this technique is complementary to other structural biology methods such as x-ray crystallography, NMR and cryo-electron microscopy[1]. The extension of traditional quantitative proteomics methods with chemical cross-linking can provide information on the structural dynamics of protein structures and protein complexes. The identification and quantitation of cross-linked peptides remains challenging for the general community, requiring specialized expertise ultimately limiting more widespread adoption of the technique. We describe a general method for targeted quantitative mass spectrometric analysis of cross-linked peptide pairs. We report the adaptation of the widely used, open source software package Skyline, for the analysis of quantitative XL-MS data as a means for data analysis and sharing of methods. We demonstrate the utility and robustness of the method with a cross-laboratory study and present data that is supported by and validates previously published data on quantified cross-linked peptide pairs. This advance provides an easy to use resource so that any lab with access to a LC-MS system capable of performing targeted quantitative analysis can quickly and accurately measure dynamic changes in protein structure and protein interactions.

  7. The Metabolomic Profile of Umbilical Cord Blood in Neonatal Hypoxic Ischaemic Encephalopathy

    PubMed Central

    Walsh, Brian H.; Broadhurst, David I.; Mandal, Rupasri; Wishart, David S.; Boylan, Geraldine B.; Kenny, Louise C.; Murray, Deirdre M.

    2012-01-01

    Background 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. Methods and Findings 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. Conclusion This study shows that a multi-platform targeted approach to

  8. Impact of exercise on fecal and cecal metabolome over aging: a longitudinal study in rats.

    PubMed

    Deda, Olga; Gika, Helen; Panagoulis, Theodoros; Taitzoglou, Ioannis; Raikos, Nikolaos; Theodoridis, Georgios

    2017-01-01

    Physical exercise can reduce adverse conditions during aging, while both exercise and aging act as metabolism modifiers. The present study investigates rat fecal and cecal metabolome alterations derived from exercise during rats' lifespan. Groups of rats trained life-long or for a specific period of time were under study. The training protocol consisted of swimming, 15-18 min per day, 3-5 days per week, with load of 4-0% of rat's weight. Fecal samples and cecal extracts were analyzed by targeted and untargeted metabolic profiling methods (GC-MS and LC-MS/MS). Effects of exercise and aging on the rats' fecal and cecal metabolome were observed. Fecal and cecal metabolomics are a promising field to investigate exercise biochemistry and age-related alterations.

  9. Changes in the Metabolome in Response to Low-Dose Exposure to Environmental Chemicals Used in Personal Care Products during Different Windows of Susceptibility.

    PubMed

    Houten, Sander M; Chen, Jia; Belpoggi, Fiorella; Manservisi, Fabiana; Sánchez-Guijo, Alberto; Wudy, Stefan A; Teitelbaum, Susan L

    2016-01-01

    The consequences of ubiquitous exposure to environmental chemicals remain poorly defined. Non-targeted metabolomic profiling is an emerging method to identify biomarkers of the physiological response to such exposures. We investigated the effect of three commonly used ingredients in personal care products, diethyl phthalate (DEP), methylparaben (MPB) and triclosan (TCS), on the blood metabolome of female Sprague-Dawley rats. Animals were treated with low levels of these chemicals comparable to human exposures during prepubertal and pubertal windows as well as chronically from birth to adulthood. Non-targeted metabolomic profiling revealed that most of the variation in the metabolites was associated with developmental stage. The low-dose exposure to DEP, MPB and TCS had a relatively small, but detectable impact on the metabolome. Multiple metabolites that were affected by chemical exposure belonged to the same biochemical pathways including phenol sulfonation and metabolism of pyruvate, lyso-plasmalogens, unsaturated fatty acids and serotonin. Changes in phenol sulfonation and pyruvate metabolism were most pronounced in rats exposed to DEP during the prepubertal period. Our metabolomics analysis demonstrates that human level exposure to personal care product ingredients has detectable effects on the rat metabolome. We highlight specific pathways such as sulfonation that warrant further study.

  10. Changes in the Metabolome in Response to Low-Dose Exposure to Environmental Chemicals Used in Personal Care Products during Different Windows of Susceptibility

    PubMed Central

    Chen, Jia; Belpoggi, Fiorella; Manservisi, Fabiana; Sánchez-Guijo, Alberto; Wudy, Stefan A.; Teitelbaum, Susan L.

    2016-01-01

    The consequences of ubiquitous exposure to environmental chemicals remain poorly defined. Non-targeted metabolomic profiling is an emerging method to identify biomarkers of the physiological response to such exposures. We investigated the effect of three commonly used ingredients in personal care products, diethyl phthalate (DEP), methylparaben (MPB) and triclosan (TCS), on the blood metabolome of female Sprague-Dawley rats. Animals were treated with low levels of these chemicals comparable to human exposures during prepubertal and pubertal windows as well as chronically from birth to adulthood. Non-targeted metabolomic profiling revealed that most of the variation in the metabolites was associated with developmental stage. The low-dose exposure to DEP, MPB and TCS had a relatively small, but detectable impact on the metabolome. Multiple metabolites that were affected by chemical exposure belonged to the same biochemical pathways including phenol sulfonation and metabolism of pyruvate, lyso-plasmalogens, unsaturated fatty acids and serotonin. Changes in phenol sulfonation and pyruvate metabolism were most pronounced in rats exposed to DEP during the prepubertal period. Our metabolomics analysis demonstrates that human level exposure to personal care product ingredients has detectable effects on the rat metabolome. We highlight specific pathways such as sulfonation that warrant further study. PMID:27467775

  11. Training in metabolomics research. I. Designing the experiment, collecting and extracting samples and generating metabolomics data

    PubMed Central

    Barnes, Stephen; Benton, H. Paul; Casazza, Krista; Cooper, Sara J.; Cui, Xiangqin; Du, Xiuxia; Engler, Jeffrey; Kabarowski, Janusz H.; Li, Shuzhao; Pathmasiri, Wimal; Prasain, Jeevan K.; Renfrow, Matthew B.; Tiwari, Hemant K.

    2016-01-01

    The study of metabolism has had a long history. Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. The National Institutes of Health Common Fund Metabolomics Program was established in 2012 to stimulate interest in the approaches and technologies of metabolomics. To deliver one of the program’s goals, the University of Alabama at Birmingham has hosted an annual 4-day short course in metabolomics for faculty, postdoctoral fellows and graduate students from national and international institutions. This paper is the first part of a summary of the training materials presented in the course to be used as a resource for all those embarking on metabolomics research. PMID:27434804

  12. Non-targeted metabolomics and lipidomics LC-MS data from maternal plasma of 180 healthy pregnant women.

    PubMed

    Luan, Hemi; Meng, Nan; Liu, Ping; Fu, Jin; Chen, Xiaomin; Rao, Weiqiao; Jiang, Hui; Xu, Xun; Cai, Zongwei; Wang, Jun

    2015-01-01

    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. 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. As a relatively large scale, real-world dataset with robust numbers of quality control samples, the data are expected to prove useful for algorithm optimization and development, with the potential to augment studies into abnormal pregnancy. All data and ISA-TAB format enriched metadata are available for download in the MetaboLights and GigaScience databases.

  13. Metabolomic characterization of laborers exposed to welding fumes.

    PubMed

    Wang, Kuo-Ching; Kuo, Ching-Hua; Tian, Tze-Feng; Tsai, Mong-Hsun; Chiung, Yin-Mei; Hsiech, Chun-Ming; Tsai, Sung-Jeng; Wang, San-Yuan; Tsai, Dong-Ming; Huang, Chiang-Ching; Tseng, Y Jane

    2012-03-19

    The complex composition of welding fumes, multiplicity of molecular targets, diverse cellular effects, and lifestyles associated with laborers vastly complicate the assessment of welding fume exposure. The urinary metabolomic profiles of 35 male welders and 16 male office workers at a Taiwanese shipyard were characterized via (1)H NMR spectroscopy and pattern recognition methods. Blood samples for the same 51 individuals were also collected, and the expression levels of the cytokines and other inflammatory markers were examined. This study dichotomized the welding exposure variable into high (welders) versus low (office workers) exposures to examine the differences of continuous outcome markers-metabolites and inflammatory markers-between the two groups. Fume particle assessments showed that welders were exposed to different concentrations of chromium, nickel, and manganese particles. Multivariate statistical analysis of urinary metabolomic patterns showed higher levels of glycine, taurine, betaine/TMAO, serine, S-sulfocysteine, hippurate, gluconate, creatinine, and acetone and lower levels of creatine among welders, while only TNF-α was significantly associated with welding fume exposure among all cytokines and other inflammatory markers measured. Of the identified metabolites, the higher levels of glycine, taurine, and betaine among welders were suspected to play some roles in modulating inflammatory and oxidative tissue injury processes. In this metabolomics experiment, we also discovered that the association of the identified metabolites with welding exposure was confounded by smoking, but not with drinking, which is a finding consistent with known modified response of inflammatory markers among smokers. Our results correspond with prior studies that utilized nonmetabolomic analytical techniques and suggest that the metabolomic profiling is an efficient method to characterize the overall effect of welding fume exposure and other confounders. © 2012 American

  14. METABOLOMICS IN MEDICAL SCIENCES--TRENDS, CHALLENGES AND PERSPECTIVES.

    PubMed

    Klupczyńska, Agnieszka; Dereziński, Paweł; Kokot, Zenon J

    2015-01-01

    Metabolomics is the latest of the "omic" technologies that involves comprehensive analysis of small molecule metabolites of an organism or a specific biological sample. Metabolomics provides an insight into the cell status and describes an actual health condition of organisms. Analysis of metabolome offers a unique opportunity to study the influence of genetic variation, disease, applied treatment or diet on endogenous metabolic state of organisms. There are many areas that might benefit from metabolomic research. In the article some applications of this novel "omic" technology in the field of medical sciences are presented. One of the most popular aims of metabolomic studies is biomarker discovery. Despite using the state-of-art analytical techniques along with advanced bioinformatic tools, metabolomic experiments encounter numerous difficulties and pitfalls. Challenges that researchers in the field of analysis of metabolome have to face include i.a., technical limitations, bioinformatic challenges and integration with other "omic" sciences. One of the grand challenges for studies in the field of metabolomics is to tackle the problem of data analysis, which is probably the most time consuming stage of metabolomic workflow and requires close collaboration between analysts, clinicians and experts in chemometric analysis. Implementation of metabolomics into clinical practice will be dependent on establishment of standardized protocols in analytical performance and data analysis and development of fit-for-purpose biomarker method validation. Metabolomics allows to achieve a sophisticated level of information about biological systems and opens up new perspectives in many fields of medicine, especially in oncology. Apart from its extensive cognitive significance, metabolomics manifests also a practical importance as it may lead to design of new non-invasive, sensitive and specific diagnostic techniques and development of new therapies.

  15. Metabolomic Profiles of Dinophysis acuminata and Dinophysis acuta Using Non-Targeted High-Resolution Mass Spectrometry: Effect of Nutritional Status and Prey.

    PubMed

    García-Portela, María; Reguera, Beatriz; Sibat, Manoella; Altenburger, Andreas; Rodríguez, Francisco; Hess, Philipp

    2018-04-26

    Photosynthetic species of the genus Dinophysis are obligate mixotrophs with temporary plastids (kleptoplastids) that are acquired from the ciliate Mesodinium rubrum , which feeds on cryptophytes of the Teleaulax-Plagioselmis-Geminigera clade. A metabolomic study of the three-species food chain Dinophysis-Mesodinium-Teleaulax was carried out using mass spectrometric analysis of extracts of batch-cultured cells of each level of that food chain. The main goal was to compare the metabolomic expression of Galician strains of Dinophysis acuminata and D. acuta that were subjected to different feeding regimes (well-fed and prey-limited) and feeding on two Mesodinium (Spanish and Danish) strains. Both Dinophysis species were able to grow while feeding on both Mesodinium strains, although differences in growth rates were observed. Toxin and metabolomic profiles of the two Dinophysis species were significantly different, and also varied between different feeding regimes and different prey organisms. Furthermore, significantly different metabolomes were expressed by a strain of D. acuminata that was feeding on different strains of the ciliate Mesodinium rubrum . Both species-specific metabolites and those common to D. acuminata and D. acuta were tentatively identified by screening of METLIN and Marine Natural Products Dictionary databases. This first metabolomic study applied to Dinophysis acuminata and D.acuta in culture establishes a basis for the chemical inventory of these species.

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

    PubMed Central

    Jiménez-Girón, Ana; Muñoz-González, Irene; Martín-Álvarez, Pedro J.; Moreno-Arribas, María Victoria; Bartolomé, Begoña

    2014-01-01

    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. PMID:25532710

  17. Training in metabolomics research. I. Designing the experiment, collecting and extracting samples and generating metabolomics data.

    PubMed

    Barnes, Stephen; Benton, H Paul; Casazza, Krista; Cooper, Sara J; Cui, Xiangqin; Du, Xiuxia; Engler, Jeffrey; Kabarowski, Janusz H; Li, Shuzhao; Pathmasiri, Wimal; Prasain, Jeevan K; Renfrow, Matthew B; Tiwari, Hemant K

    2016-07-01

    The study of metabolism has had a long history. Metabolomics, a systems biology discipline representing analysis of known and unknown pathways of metabolism, has grown tremendously over the past 20 years. Because of its comprehensive nature, metabolomics requires careful consideration of the question(s) being asked, the scale needed to answer the question(s), collection and storage of the sample specimens, methods for extraction of the metabolites from biological matrices, the analytical method(s) to be employed and the quality control of the analyses, how collected data are correlated, the statistical methods to determine metabolites undergoing significant change, putative identification of metabolites and the use of stable isotopes to aid in verifying metabolite identity and establishing pathway connections and fluxes. The National Institutes of Health Common Fund Metabolomics Program was established in 2012 to stimulate interest in the approaches and technologies of metabolomics. To deliver one of the program's goals, the University of Alabama at Birmingham has hosted an annual 4-day short course in metabolomics for faculty, postdoctoral fellows and graduate students from national and international institutions. This paper is the first part of a summary of the training materials presented in the course to be used as a resource for all those embarking on metabolomics research. The complete set of training materials including slide sets and videos can be viewed at http://www.uab.edu/proteomics/metabolomics/workshop/workshop_june_2015.php. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  18. Metabolomics of Genetically Modified Crops

    PubMed Central

    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

  19. Impact of storage conditions on the urinary metabolomics fingerprint.

    PubMed

    Laparre, Jérôme; Kaabia, Zied; Mooney, Mark; Buckley, Tom; Sherry, Mark; Le Bizec, Bruno; Dervilly-Pinel, Gaud

    2017-01-25

    Urine stability during storage is essential in metabolomics to avoid misleading conclusions or erroneous interpretations. Facing the lack of comprehensive studies on urine metabolome stability, the present work performed a follow-up of potential modifications in urinary chemical profile using LC-HRMS on the basis of two parameters: the storage temperature (+4 °C, -20 °C, -80 °C and freeze-dried stored at -80 °C) and the storage duration (5-144 days). Both HILIC and RP chromatographies have been implemented in order to globally monitor the urinary metabolome. Using an original data processing associated to univariate and multivariate data analysis, our study confirms that chemical profiles of urine samples stored at +4 °C are very rapidly modified, as observed for instance for compounds such as:N-acetyl Glycine, Adenosine, 4-Amino benzoic acid, N-Amino diglycine, creatine, glucuronic acid, 3-hydroxy-benzoic acid, pyridoxal, l-pyroglutamic acid, shikimic acid, succinic acid, thymidine, trigonelline and valeryl-carnitine, while it also demonstrates that urine samples stored at -20 °C exhibit a global stability over a long period with no major modifications compared to -80 °C condition. This study is the first to investigate long term stability of urine samples and report potential modifications in the urinary metabolome, using both targeted approach monitoring individually a large number (n > 200) of urinary metabolites and an untargeted strategy enabling assessing for global impact of storage conditions. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. NMR and MS Methods for Metabolomics.

    PubMed

    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.

  1. Fecal metabolome of the Hadza hunter-gatherers: a host-microbiome integrative view

    PubMed Central

    Turroni, Silvia; Fiori, Jessica; Rampelli, Simone; Schnorr, Stephanie L.; Consolandi, Clarissa; Barone, Monica; Biagi, Elena; Fanelli, Flaminia; Mezzullo, Marco; Crittenden, Alyssa N.; Henry, Amanda G.; Brigidi, Patrizia; Candela, Marco

    2016-01-01

    The recent characterization of the gut microbiome of traditional rural and foraging societies allowed us to appreciate the essential co-adaptive role of the microbiome in complementing our physiology, opening up significant questions on how the microbiota changes that have occurred in industrialized urban populations may have altered the microbiota-host co-metabolic network, contributing to the growing list of Western diseases. Here, we applied a targeted metabolomics approach to profile the fecal metabolome of the Hadza of Tanzania, one of the world’s few remaining foraging populations, and compared them to the profiles of urban living Italians, as representative of people in the post-industrialized West. Data analysis shows that during the rainy season, when the diet is primarily plant-based, Hadza are characterized by a distinctive enrichment in hexoses, glycerophospholipids, sphingolipids, and acylcarnitines, while deplete in the most common natural amino acids and derivatives. Complementary to the documented unique metagenomic features of their gut microbiome, our findings on the Hadza metabolome lend support to the notion of an alternate microbiome configuration befitting of a nomadic forager lifestyle, which helps maintain metabolic homeostasis through an overall scarcity of inflammatory factors, which are instead highly represented in the Italian metabolome. PMID:27624970

  2. Metabolomic responses to lumacaftor/ivacaftor in cystic fibrosis.

    PubMed

    Kopp, Benjamin T; McCulloch, Scott; Shrestha, Chandra L; Zhang, Shuzhong; Sarzynski, Lisa; Woodley, Frederick W; Hayes, Don

    2018-05-01

    Cystic fibrosis (CF) is a life-limiting disease caused by a defect in the cystic fibrosis transmembrane conductance regulator (CFTR) gene. Lumacaftor/Ivacaftor is a novel CFTR modulator approved for patients that are homozygous for Phe508del CFTR, but its clinical effectiveness varies amongst patients, making it difficult to determine clinical responders. Therefore, identifying biochemical biomarkers associated with drug response are clinically important for follow-up studies. Serum metabolomics was performed on twenty patients with CF pre- and 6-month post-Lumacaftor/Ivacaftor response via Ultrahigh Performance Liquid Chromatography-Tandem Mass Spectroscopy (UPLC-MS/MS). Correlation with clinical variables was performed. Metabolomics analysis demonstrated 188 differentially regulated metabolites between patients pre- and post-Lumacaftor/Ivacaftor initiation, with a predominance of lipid and amino acid alterations. The top 30 metabolites were able to differentiate pre- and post-Lumacaftor/Ivacaftor status in greater than 90% of patients via a random-forest confusion matrix. Alterations in bile acids, phospholipids, and bacteria-associated metabolites were the predominant changes associated with drug response. Importantly, changes in metabolic patterns were associated with clinical responders. Selected key lipid and amino acid metabolic pathways were significantly affected by Lumacaftor/Ivacaftor initiation and similar pathways were affected in clinical responders. Targeted metabolomics may provide useful and relevant biomarkers of CFTR modulator responses. © 2018 Wiley Periodicals, Inc.

  3. Liquid chromatography-mass spectrometry in metabolomics research: mass analyzers in ultra high pressure liquid chromatography coupling.

    PubMed

    Forcisi, Sara; Moritz, Franco; Kanawati, Basem; Tziotis, Dimitrios; Lehmann, Rainer; Schmitt-Kopplin, Philippe

    2013-05-31

    The present review gives an introduction into the concept of metabolomics and provides an overview of the analytical tools applied in non-targeted metabolomics with a focus on liquid chromatography (LC). LC is a powerful analytical tool in the study of complex sample matrices. A further development and configuration employing Ultra-High Pressure Liquid Chromatography (UHPLC) is optimized to provide the largest known liquid chromatographic resolution and peak capacity. Reasonably UHPLC plays an important role in separation and consequent metabolite identification of complex molecular mixtures such as bio-fluids. The most sensitive detectors for these purposes are mass spectrometers. Almost any mass analyzer can be optimized to identify and quantify small pre-defined sets of targets; however, the number of analytes in metabolomics is far greater. Optimized protocols for quantification of large sets of targets may be rendered inapplicable. Results on small target set analyses on different sample matrices are easily comparable with each other. In non-targeted metabolomics there is almost no analytical method which is applicable to all different matrices due to limitations pertaining to mass analyzers and chromatographic tools. The specifications of the most important interfaces and mass analyzers are discussed. We additionally provide an exemplary application in order to demonstrate the level of complexity which remains intractable up to date. The potential of coupling a high field Fourier Transform Ion Cyclotron Resonance Mass Spectrometer (ICR-FT/MS), the mass analyzer with the largest known mass resolving power, to UHPLC is given with an example of one human pre-treated plasma sample. This experimental example illustrates one way of overcoming the necessity of faster scanning rates in the coupling with UHPLC. The experiment enabled the extraction of thousands of features (analytical signals). A small subset of this compositional space could be mapped into a mass

  4. Metabolomics: building on a century of biochemistry to guide human health

    PubMed Central

    German, J. Bruce; Hammock, Bruce D.; Watkins, Steven M.

    2006-01-01

    Medical diagnosis and treatment efficacy will improve significantly when a more personalized system for health assessment is implemented. This system will require diagnostics that provide sufficiently detailed information about the metabolic status of individuals such that assay results will be able to guide food, drug and lifestyle choices to maintain or improve distinct aspects of health without compromising others. Achieving this goal will use the new science of metabolomics – comprehensive metabolic profiling of individuals linked to the biological understanding of human integrative metabolism. Candidate technologies to accomplish this goal are largely available, yet they have not been brought into practice for this purpose. Metabolomic technologies must be sufficiently rapid, accurate and affordable to be routinely accessible to both healthy and acutely ill individuals. The use of metabolomic data to predict the health trajectories of individuals will require bioinformatic tools and quantitative reference databases. These databases containing metabolite profiles from the population must be built, stored and indexed according to metabolic and health status. Building and annotating these databases with the knowledge to predict how a specific metabolic pattern from an individual can be adjusted with diet, drugs and lifestyle to improve health represents a logical application of the biochemistry knowledge that the life sciences have produced over the past 100 years. PMID:16680201

  5. Metabolomic Fingerprinting of Romaneschi Globe Artichokes by NMR Spectroscopy and Multivariate Data Analysis.

    PubMed

    de Falco, Bruna; Incerti, Guido; Pepe, Rosa; Amato, Mariana; Lanzotti, Virginia

    2016-09-01

    Globe artichoke (Cynara cardunculus L. var. scolymus L. Fiori) and cardoon (Cynara cardunculus L. var. altilis DC) are sources of nutraceuticals and bioactive compounds. To apply a NMR metabolomic fingerprinting approach to Cynara cardunculus heads to obtain simultaneous identification and quantitation of the major classes of organic compounds. The edible part of 14 Globe artichoke populations, belonging to the Romaneschi varietal group, were extracted to obtain apolar and polar organic extracts. The analysis was also extended to one species of cultivated cardoon for comparison. The (1) H-NMR of the extracts allowed simultaneous identification of the bioactive metabolites whose quantitation have been obtained by spectral integration followed by principal component analysis (PCA). Apolar organic extracts were mainly based on highly unsaturated long chain lipids. Polar organic extracts contained organic acids, amino acids, sugars (mainly inulin), caffeoyl derivatives (mainly cynarin), flavonoids, and terpenes. The level of nutraceuticals was found to be highest in the Italian landraces Bianco di Pertosa zia E and Natalina while cardoon showed the lowest content of all metabolites thus confirming the genetic distance between artichokes and cardoon. Metabolomic approach coupling NMR spectroscopy with multivariate data analysis allowed for a detailed metabolite profile of artichoke and cardoon varieties to be obtained. Relevant differences in the relative content of the metabolites were observed for the species analysed. This work is the first application of (1) H-NMR with multivariate statistics to provide a metabolomic fingerprinting of Cynara scolymus. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

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

    PubMed

    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.

  7. Comprehensive metabolomic, lipidomic and microscopic profiling of Yarrowia lipolytica during lipid accumulation identifies targets for increased lipogenesis

    DOE PAGES

    Pomraning, Kyle R.; Wei, Siwei; Karagiosis, Sue A.; ...

    2015-04-23

    Yarrowia lipolytica is an oleaginous ascomycete yeast that accumulates large amounts of lipids and has potential as a biofuel producing organism. Despite a growing scientific literature focused on lipid production by Y. lipolytica, there remain significant knowledge gaps regarding the key biological processes involved. We applied a combination of metabolomic and lipidomic profiling approaches as well as microscopic techniques to identify and characterize the key pathways involved in de novo lipid accumulation from glucose in batch cultured, wild-type Y. lipolytica. We found that lipids accumulated rapidly and peaked at 48 hours during the five day experiment, concurrent with a shiftmore » in amino acid metabolism. We also report that Y. lipolytica secretes disaccharides early in batch culture and reabsorbs them when extracellular glucose is depleted. Exhaustion of extracellular sugars coincided with thickening of the cell wall, suggesting that genes involved in cell wall biogenesis may be a useful target for improving the efficiency of lipid producing yeast strains.« less

  8. Targeted redox and energy cofactor metabolomics in Clostridium thermocellum and Thermoanaerobacterium saccharolyticum

    DOE PAGES

    Sander, Kyle; Asano, Keiji G.; Bhandari, Deepak; ...

    2017-11-30

    Clostridium thermocellum and Thermoanaerobacterium saccharolyticum are prominent candidate biocatalysts that, together, can enable the direct biotic conversion of lignocellulosic biomass to ethanol. The imbalance and suboptimal turnover rates of redox cofactors are currently hindering engineering efforts to achieve higher bioproductivity in both organisms. Measuring relevant intracellular cofactor concentrations will help understand redox state of these cofactors and help identify a strategy to overcome these limitations; however, metabolomic determinations of these labile metabolites have historically proved challenging.Results: Through our validations, we verified the handling and storage stability of these metabolites, and verified extraction matrices and extraction solvent were not suppressing massmore » spectrometry signals. We recovered adenylate energy charge ratios (a main quality indicator) above 0.82 for all extractions. NADH/NAD+ values of 0.26 and 0.04 for an adhE-deficient strain of C. thermocellum and its parent, respectively, reflect the expected shift to a more reduced redox potential when a species lacks the ability to re-oxidize NADH by synthesizing ethanol. This method failed to yield reliable results with C. bescii and poor-growing strains of T. saccharolyticum. Lastly, our validated protocols demonstrate and validate the extraction and analysis of selected redox and energy-related metabolites from two candidate consolidated bioprocessing biocatalysts, C. thermocellum and T. saccharolyticum. This development and validation highlights the important, but often neglected, need to optimize and validate metabolomic protocols when adapting them to new cell or tissue types.« less

  9. Targeted redox and energy cofactor metabolomics in Clostridium thermocellum and Thermoanaerobacterium saccharolyticum

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Sander, Kyle; Asano, Keiji G.; Bhandari, Deepak

    Clostridium thermocellum and Thermoanaerobacterium saccharolyticum are prominent candidate biocatalysts that, together, can enable the direct biotic conversion of lignocellulosic biomass to ethanol. The imbalance and suboptimal turnover rates of redox cofactors are currently hindering engineering efforts to achieve higher bioproductivity in both organisms. Measuring relevant intracellular cofactor concentrations will help understand redox state of these cofactors and help identify a strategy to overcome these limitations; however, metabolomic determinations of these labile metabolites have historically proved challenging.Results: Through our validations, we verified the handling and storage stability of these metabolites, and verified extraction matrices and extraction solvent were not suppressing massmore » spectrometry signals. We recovered adenylate energy charge ratios (a main quality indicator) above 0.82 for all extractions. NADH/NAD+ values of 0.26 and 0.04 for an adhE-deficient strain of C. thermocellum and its parent, respectively, reflect the expected shift to a more reduced redox potential when a species lacks the ability to re-oxidize NADH by synthesizing ethanol. This method failed to yield reliable results with C. bescii and poor-growing strains of T. saccharolyticum. Lastly, our validated protocols demonstrate and validate the extraction and analysis of selected redox and energy-related metabolites from two candidate consolidated bioprocessing biocatalysts, C. thermocellum and T. saccharolyticum. This development and validation highlights the important, but often neglected, need to optimize and validate metabolomic protocols when adapting them to new cell or tissue types.« less

  10. A Plasma Metabolomic Signature of the Exfoliation Syndrome Involves Amino Acids, Acylcarnitines, and Polyamines.

    PubMed

    Leruez, Stéphanie; Bresson, Thomas; Chao de la Barca, Juan M; Marill, Alexandre; de Saint Martin, Grégoire; Buisset, Adrien; Muller, Jeanne; Tessier, Lydie; Gadras, Cédric; Verny, Christophe; Amati-Bonneau, Patrizia; Lenaers, Guy; Gohier, Philippe; Bonneau, Dominique; Simard, Gilles; Milea, Dan; Procaccio, Vincent; Reynier, Pascal

    2018-02-01

    To determine the plasma metabolomic signature of the exfoliative syndrome (XFS), the most common cause worldwide of secondary open-angle glaucoma. We performed a targeted metabolomic study, using the standardized p180 Biocrates Absolute IDQ p180 kit with a QTRAP 5500 mass spectrometer, to compare the metabolomic profiles of plasma from individuals with XFS (n = 16), and an age- and sex-matched control group with cataract (n = 18). A total of 151 metabolites were detected correctly, 16 of which allowed for construction of an OPLS-DA model with a good predictive capability (Q2cum = 0.51) associated with a low risk of over-fitting (permQ2 = -0.48, CV-ANOVA P-value <0.001). The metabolites contributing the most to the signature were octanoyl-carnitine (C8) and decanoyl-carnitine (C10), the branched-chain amino acids (i.e., isoleucine, leucine, and valine), and tyrosine, all of which were at higher concentrations in the XFS group, whereas spermine and spermidine, together with their precursor acetyl-ornithine, were at lower concentrations than in the control group. We identified a significant metabolomic signature in the plasma of individuals with XFS. Paradoxically, this signature, characterized by lower concentrations of the neuroprotective spermine and spermidine polyamines than in controls, partially overlaps the plasma metabolomic profile associated with insulin resistance, despite the absence of evidence of insulin resistance in XFS.

  11. Metabolomic mapping of cancer stem cells for reducing and exploiting tumor heterogeneity.

    PubMed

    Cuyàs, Elisabet; Verdura, Sara; Fernández-Arroyo, Salvador; Bosch-Barrera, Joaquim; Martin-Castillo, Begoña; Joven, Jorge; Menendez, Javier A

    2017-11-21

    Personalized cancer medicine based on the analysis of tumors en masse is limited by tumor heterogeneity, which has become a major obstacle to effective cancer treatment. Cancer stem cells (CSC) are emerging as key drivers of inter- and intratumoral heterogeneity. CSC have unique metabolic dependencies that are required not only for specific bioenergetic/biosynthetic demands but also for sustaining their operational epigenetic traits, i.e. self-renewal, tumor-initiation, and plasticity. Given that the metabolome is the final downstream product of all the -omic layers and, therefore, most representative of the biological phenotype, we here propose that a novel approach to better understand the complexity of tumor heterogeneity is by mapping and cataloging small numbers of CSC metabolomic phenotypes. The narrower metabolomic diversity of CSC states could be employed to reduce multidimensional tumor heterogeneity into dynamic models of fewer actionable sub-phenotypes. The identification of the driver nodes that are used differentially by CSC states to metabolically regulate self-renewal and tumor initation and escape chemotherapy might open new preventive and therapeutic avenues. The mapping of CSC metabolomic states could become a pioneering strategy to reduce the dimensionality of tumor heterogeneity and improve our ability to examine changes in tumor cell populations for cancer detection, prognosis, prediction/monitoring of therapy response, and detection of therapy resistance and recurrent disease. The identification of driver metabolites and metabolic nodes accounting for a large amount of variance within the CSC metabolomic sub-phenotypes might offer new unforeseen opportunities for reducing and exploiting tumor heterogeneity via metabolic targeting of CSC.

  12. Urine metabolomics.

    PubMed

    Zhang, Aihua; Sun, Hui; Wu, Xiuhong; Wang, Xijun

    2012-12-24

    Metabolomics is a powerful technique for the discovery of novel biomarkers and elucidation of biochemical pathways to improve diagnosis, prognosis and therapy. An advantage of this approach is its ability to assess global metabolic profiles to enhance pathologic characterization. Urine is an ideal bio-medium for disease study because it is readily available, easily obtained and less complex than other body fluids. Ease of collection allows for serial sampling to monitor disease and therapeutic response. Because of this potential, this paper will review urine metabolomic analysis, discuss its significance in the post-genomic era and highlight the specific roles of endogenous small molecule metabolites in this emerging field. Copyright © 2012 Elsevier B.V. All rights reserved.

  13. Quantitative metabolomics by H-NMR and LC-MS/MS confirms altered metabolic pathways in diabetes.

    PubMed

    Lanza, Ian R; Zhang, Shucha; Ward, Lawrence E; Karakelides, Helen; Raftery, Daniel; Nair, K Sreekumaran

    2010-05-10

    Insulin is as a major postprandial hormone with profound effects on carbohydrate, fat, and protein metabolism. In the absence of exogenous insulin, patients with type 1 diabetes exhibit a variety of metabolic abnormalities including hyperglycemia, glycosurea, accelerated ketogenesis, and muscle wasting due to increased proteolysis. We analyzed plasma from type 1 diabetic (T1D) humans during insulin treatment (I+) and acute insulin deprivation (I-) and non-diabetic participants (ND) by (1)H nuclear magnetic resonance spectroscopy and liquid chromatography-tandem mass spectrometry. The aim was to determine if this combination of analytical methods could provide information on metabolic pathways known to be altered by insulin deficiency. Multivariate statistics differentiated proton spectra from I- and I+ based on several derived plasma metabolites that were elevated during insulin deprivation (lactate, acetate, allantoin, ketones). Mass spectrometry revealed significant perturbations in levels of plasma amino acids and amino acid metabolites during insulin deprivation. Further analysis of metabolite levels measured by the two analytical techniques indicates several known metabolic pathways that are perturbed in T1D (I-) (protein synthesis and breakdown, gluconeogenesis, ketogenesis, amino acid oxidation, mitochondrial bioenergetics, and oxidative stress). This work demonstrates the promise of combining multiple analytical methods with advanced statistical methods in quantitative metabolomics research, which we have applied to the clinical situation of acute insulin deprivation in T1D to reflect the numerous metabolic pathways known to be affected by insulin deficiency.

  14. Development of chemical isotope labeling liquid chromatography mass spectrometry for silkworm hemolymph metabolomics.

    PubMed

    Shen, Weifeng; Han, Wei; Li, Yunong; Meng, Zhiqi; Cai, Leiming; Li, Liang

    2016-10-26

    Silkworm (Bombyx mori) is a very useful target insect for evaluation of endocrine disruptor chemicals (EDCs) due to mature breeding techniques, complete endocrine system and broad basic knowledge on developmental biology. Comparative metabolomics of silkworms with and without EDC exposure offers another dimension of studying EDCs. In this work, we report a workflow on metabolomic profiling of silkworm hemolymph based on high-performance chemical isotope labeling (CIL) liquid chromatography mass spectrometry (LC-MS) and demonstrate its application in studying the metabolic changes associated with the pesticide dichlorodiphenyltrichloroethane (DDT) exposure in silkworm. Hemolymph samples were taken from mature silkworms after growing on diet that contained DDT at four different concentrations (1, 0.1, 0.01, 0.001 ppm) as well as on diet without DDT as controls. They were subjected to differential 12 C-/ 13 C-dansyl labeling of the amine/phenol submetabolome, LC-UV quantification of the total amount of labeled metabolites for sample normalization, and LC-MS detection and relative quantification of individual metabolites in comparative samples. The total concentration of labeled metabolites did not show any significant change between four DDT-treatment groups and one control group. Multivariate statistical analysis of the metabolome data set showed that there was a distinct metabolomic separation between the five groups. Out of the 2044 detected peak pairs, 338 and 1471 metabolites have been putatively identified against the HMDB database and the EML library, respectively. 65 metabolites were identified by the dansyl library searching based on the accurate mass and retention time. Among the 65 identified metabolites, 33 positive metabolites had changes of greater than 1.20-fold or less than 0.83-fold in one or more groups with p-value of smaller than 0.05. Several useful biomarkers including serine, methionine, tryptophan, asymmetric dimethylarginine, N

  15. Metabolomics for secondary metabolite research.

    PubMed

    Breitling, Rainer; Ceniceros, Ana; Jankevics, Andris; Takano, Eriko

    2013-11-11

    Metabolomics, the global characterization of metabolite profiles, is becoming an increasingly powerful tool for research on secondary metabolite discovery and production. In this review we discuss examples of recent technological advances and biological applications of metabolomics in the search for chemical novelty and the engineered production of bioactive secondary metabolites.

  16. Antibody Drug Conjugates: Application of Quantitative Pharmacology in Modality Design and Target Selection.

    PubMed

    Sadekar, S; Figueroa, I; Tabrizi, M

    2015-07-01

    Antibody drug conjugates (ADCs) are a multi-component modality comprising of an antibody targeting a cell-specific antigen, a potent drug/payload, and a linker that can be processed within cellular compartments to release payload upon internalization. Numerous ADCs are being evaluated in both research and clinical settings within the academic and pharmaceutical industry due to their ability to selectively deliver potent payloads. Hence, there is a clear need to incorporate quantitative approaches during early stages of drug development for effective modality design and target selection. In this review, we describe a quantitative approach and framework for evaluation of the interplay between drug- and systems-dependent properties (i.e., target expression, density, localization, turnover, and affinity) in order to deliver a sufficient amount of a potent payload into the relevant target cells. As discussed, theoretical approaches with particular considerations given to various key properties for the target and modality suggest that delivery of the payload into particular effect cells to be more sensitive to antigen concentrations for targets with slow turnover rates as compared to those with faster internalization rates. Further assessments also suggest that increasing doses beyond the threshold of the target capacity (a function of target internalization and expression) may not impact the maximum amount of payload delivered to the intended effect cells. This article will explore the important application of quantitative sciences in selection of the target and design of ADC modalities.

  17. An overview of renal metabolomics.

    PubMed

    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.

  18. Natural isotope correction of MS/MS measurements for metabolomics and (13)C fluxomics.

    PubMed

    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.

  19. Serial Metabolome Changes in a Prospective Cohort of Subjects with Influenza Viral Infection and Comparison with Dengue Fever.

    PubMed

    Cui, Liang; Fang, Jinling; Ooi, Eng Eong; Lee, Yie Hou

    2017-07-07

    Influenza virus infection (IVI) and dengue virus infection (DVI) are major public health threats. Between IVI and DVI, clinical symptoms can be overlapping yet infection-specific, but host metabolome changes are not well-described. Untargeted metabolomics and targeted oxylipinomic analyses were performed on sera serially collected at three phases of infection from a prospective cohort study of adult subjects with either H3N2 influenza infection or dengue fever. Untargeted metabolomics identified 26 differential metabolites, and major perturbed pathways included purine metabolism, fatty acid biosynthesis and β-oxidation, tryptophan metabolism, phospholipid catabolism, and steroid hormone pathway. Alterations in eight oxylipins were associated with the early symptomatic phase of H3N2 flu infection, were mostly arachidonic acid-derived, and were enriched in the lipoxygenase pathway. There was significant overlap in metabolome profiles in both infections. However, differences specific to IVI and DVI were observed. DVI specifically attenuated metabolites including serotonin, bile acids and biliverdin. Additionally, metabolome changes were more persistent in IVI in which metabolites such as hypoxanthine, inosine, and xanthine of the purine metabolism pathway remained significantly elevated at 21-27 days after fever onset. This study revealed the dynamic metabolome changes in IVI subjects and provided biochemical insights on host physiological similarities and differences between IVI and DVI.

  20. Epitope mapping and targeted quantitation of the cardiac biomarker troponin by SID-MRM mass spectrometry.

    PubMed

    Zhao, Cheng; Trudeau, Beth; Xie, Helen; Prostko, John; Fishpaugh, Jeffrey; Ramsay, Carol

    2014-06-01

    The absolute quantitation of the targeted protein using MS provides a promising method to evaluate/verify biomarkers used in clinical diagnostics. In this study, a cardiac biomarker, troponin I (TnI), was used as a model protein for method development. The epitope peptide of TnI was characterized by epitope excision followed with LC/MS/MS method and acted as the surrogate peptide for the targeted protein quantitation. The MRM-based MS assay using a stable internal standard that improved the selectivity, specificity, and sensitivity of the protein quantitation. Also, plasma albumin depletion and affinity enrichment of TnI by anti-TnI mAb-coated microparticles reduced the sample complexity, enhanced the dynamic range, and further improved the detecting sensitivity of the targeted protein in the biological matrix. Therefore, quantitation of TnI, a low abundant protein in human plasma, has demonstrated the applicability of the targeted protein quantitation strategy through its epitope peptide determined by epitope mapping method. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  1. Metabolome analysis for discovering biomarkers of gastroenterological cancer.

    PubMed

    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.

  2. Metabolomics of cancer cell cultures to assess the effects of dietary phytochemicals.

    PubMed

    Brasili, Elisa; Filho, Valdir Cechinel

    2017-05-03

    Cancer is a multi-factorial disease and is a major cause of morbidity and mortality worldwide. Dietary phytochemicals have been used for the treatment of cancer throughout history due to their safety, low toxicity, and general availability. Several studies have been performed to elucidate the effects of dietary phytochemicals on cancer metabolism, and many molecular targets of phytochemicals have been discovered. In spite of remarkable progress, their effects on cancer metabolism have not yet been fully clarified. Recent developments in metabolomics allowed to probe much further the metabolism of cancer, highlighting altered metabolic pathways and offering a new powerful tool to investigate cancer disease. In this review, we discuss the main metabolic alterations of cancer cells and the potentiality of phytochemicals as promising modulators of cancer metabolism. We will focus on the application of nuclear magnetic resonance-based metabolomics on breast and hepatocellular cancer cell lines to evaluate the impact of curcumin and resveratrol on cancer metabolome with the aim to demonstrate the premise of this approach to provide useful information for a better understanding of impact of diet components on cancer disease.

  3. Metabolomics: beyond biomarkers and towards mechanisms

    PubMed Central

    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

  4. An overview of plant volatile metabolomics, sample treatment and reporting considerations with emphasis on mechanical damage and biological control of weeds.

    PubMed

    Beck, John J; Smith, Lincoln; Baig, Nausheena

    2014-01-01

    The technology for the collection and analysis of plant-emitted volatiles for understanding chemical cues of plant-plant, plant-insect or plant-microbe interactions has increased over the years. Consequently, the in situ collection, analysis and identification of volatiles are considered integral to elucidation of complex plant communications. Due to the complexity and range of emissions the conditions for consistent emission of volatiles are difficult to standardise. To discuss: evaluation of emitted volatile metabolites as a means of screening potential target- and non-target weeds/plants for insect biological control agents; plant volatile metabolomics to analyse resultant data; importance of considering volatiles from damaged plants; and use of a database for reporting experimental conditions and results. Recent literature relating to plant volatiles and plant volatile metabolomics are summarised to provide a basic understanding of how metabolomics can be applied to the study of plant volatiles. An overview of plant secondary metabolites, plant volatile metabolomics, analysis of plant volatile metabolomics data and the subsequent input into a database, the roles of plant volatiles, volatile emission as a function of treatment, and the application of plant volatile metabolomics to biological control of invasive weeds. It is recommended that in addition to a non-damaged treatment, plants be damaged prior to collecting volatiles to provide the greatest diversity of odours. For the model system provided, optimal volatile emission occurred when the leaf was punctured with a needle. Results stored in a database should include basic environmental conditions or treatments. Copyright © 2013 John Wiley & Sons, Ltd.

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

    PubMed

    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.

  6. Bridging the gap: basic metabolomics methods for natural product chemistry.

    PubMed

    Jones, Oliver A H; Hügel, Helmut M

    2013-01-01

    Natural products and their derivatives often have potent physiological activities and therefore play important roles as both frontline treatments for many diseases and as the inspiration for chemically synthesized therapeutics. However, the detection and synthesis of new therapeutic compounds derived from, or inspired by natural compounds has declined in recent years due to the increased difficulty of identifying and isolating novel active compounds. A new strategy is therefore necessary to jumpstart this field of research. Metabolomics, including both targeted and global metabolite profiling strategies, has the potential to be instrumental in this effort since it allows a systematic study of complex mixtures (such as plant extracts) without the need for prior isolation of active ingredients (or mixtures thereof). Here we describe the basic steps for conducting metabolomics experiments and analyzing the results using some of the more commonly used analytical and statistical methodologies.

  7. Basics of mass spectrometry based metabolomics.

    PubMed

    Courant, Frédérique; Antignac, Jean-Philippe; Dervilly-Pinel, Gaud; Le Bizec, Bruno

    2014-11-01

    The emerging field of metabolomics, aiming to characterize small molecule metabolites present in biological systems, promises immense potential for different areas such as medicine, environmental sciences, agronomy, etc. The purpose of this article is to guide the reader through the history of the field, then through the main steps of the metabolomics workflow, from study design to structure elucidation, and help the reader to understand the key phases of a metabolomics investigation and the rationale underlying the protocols and techniques used. This article is not intended to give standard operating procedures as several papers related to this topic were already provided, but is designed as a tutorial aiming to help beginners understand the concept and challenges of MS-based metabolomics. A real case example is taken from the literature to illustrate the application of the metabolomics approach in the field of doping analysis. Challenges and limitations of the approach are then discussed along with future directions in research to cope with these limitations. This tutorial is part of the International Proteomics Tutorial Programme (IPTP18). © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  8. Translating Metabolomics to Cardiovascular Biomarkers

    PubMed Central

    Senn, Todd; Hazen, Stanley L.; Tang, W. H. Wilson

    2012-01-01

    Metabolomics is the systematic study of the unique chemical fingerprints of small-molecules, or metabolite profiles, that are related to a variety of cellular metabolic processes in a cell, organ, or organism. While mRNA gene expression data and proteomic analyses do not tell the whole story of what might be happening in a cell, metabolic profiling provides direct and indirect physiologic insights that can potentially be detectable in a wide range of biospecimens. Although not specific to cardiac conditions, translating metabolomics to cardiovascular biomarkers has followed the traditional path of biomarker discovery from identification and confirmation to clinical validation and bedside testing. With technological advances in metabolomic tools (such as nuclear magnetic resonance spectroscopy and mass spectrometry) and more sophisticated bioinformatics and analytical techniques, the ability to measure low-molecular-weight metabolites in biospecimens provides a unique insight into established and novel metabolic pathways. Systemic metabolomics may provide physiologic understanding of cardiovascular disease states beyond traditional profiling, and may involve descriptions of metabolic responses of an individual or population to therapeutic interventions or environmental exposures. PMID:22824112

  9. Mathematical Modeling Approaches in Plant Metabolomics.

    PubMed

    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.

  10. The mzTab Data Exchange Format: Communicating Mass-spectrometry-based Proteomics and Metabolomics Experimental Results to a Wider Audience*

    PubMed Central

    Griss, Johannes; Jones, Andrew R.; Sachsenberg, Timo; Walzer, Mathias; Gatto, Laurent; Hartler, Jürgen; Thallinger, Gerhard G.; Salek, Reza M.; Steinbeck, Christoph; Neuhauser, Nadin; Cox, Jürgen; Neumann, Steffen; Fan, Jun; Reisinger, Florian; Xu, Qing-Wei; del Toro, Noemi; Pérez-Riverol, Yasset; Ghali, Fawaz; Bandeira, Nuno; Xenarios, Ioannis; Kohlbacher, Oliver; Vizcaíno, Juan Antonio; Hermjakob, Henning

    2014-01-01

    The HUPO Proteomics Standards Initiative has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS)-based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools such as Microsoft Excel or R. We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplemental material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. These range from a simple summary of the final results to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found online. PMID:24980485

  11. Cold acclimation wholly reorganizes the Drosophila melanogaster transcriptome and metabolome

    PubMed Central

    MacMillan, Heath A.; Knee, Jose M.; Dennis, Alice B.; Udaka, Hiroko; Marshall, Katie E.; Merritt, Thomas J. S.; Sinclair, Brent J.

    2016-01-01

    Cold tolerance is a key determinant of insect distribution and abundance, and thermal acclimation can strongly influence organismal stress tolerance phenotypes, particularly in small ectotherms like Drosophila. However, there is limited understanding of the molecular and biochemical mechanisms that confer such impressive plasticity. Here, we use high-throughput mRNA sequencing (RNA-seq) and liquid chromatography – mass spectrometry (LC-MS) to compare the transcriptomes and metabolomes of D. melanogaster acclimated as adults to warm (rearing) (21.5 °C) or cold conditions (6 °C). Cold acclimation improved cold tolerance and led to extensive biological reorganization: almost one third of the transcriptome and nearly half of the metabolome were differentially regulated. There was overlap in the metabolic pathways identified via transcriptomics and metabolomics, with proline and glutathione metabolism being the most strongly-supported metabolic pathways associated with increased cold tolerance. We discuss several new targets in the study of insect cold tolerance (e.g. dopamine signaling and Na+-driven transport), but many previously identified candidate genes and pathways (e.g. heat shock proteins, Ca2+ signaling, and ROS detoxification) were also identified in the present study, and our results are thus consistent with and extend the current understanding of the mechanisms of insect chilling tolerance. PMID:27357258

  12. Metabolomic biomarkers correlating with hepatic lipidosis in dairy cows.

    PubMed

    Imhasly, Sandro; Naegeli, Hanspeter; Baumann, Sven; von Bergen, Martin; Luch, Andreas; Jungnickel, Harald; Potratz, Sarah; Gerspach, Christian

    2014-06-02

    Hepatic lipidosis or fatty liver disease is a major metabolic disorder of high-producing dairy cows that compromises animal performance and, hence, causes heavy economic losses worldwide. This syndrome, occurring during the critical transition from gestation to early lactation, leads to an impaired health status, decreased milk yield, reduced fertility and shortened lifetime. Because the prevailing clinical chemistry parameters indicate advanced liver damage independently of the underlying disease, currently, hepatic lipidosis can only be ascertained by liver biopsy. We hypothesized that the condition of fatty liver disease may be accompanied by an altered profile of endogenous metabolites in the blood of affected animals. To identify potential small-molecule biomarkers as a novel diagnostic alternative, the serum samples of diseased dairy cows were subjected to a targeted metabolomics screen by triple quadrupole mass spectrometry. A subsequent multivariate test involving principal component and linear discriminant analyses yielded 29 metabolites (amino acids, phosphatidylcholines and sphingomyelines) that, in conjunction, were able to distinguish between dairy cows with no hepatic lipidosis and those displaying different stages of the disorder. This proof-of-concept study indicates that metabolomic profiles, including both amino acids and lipids, distinguish hepatic lipidosis from other peripartal disorders and, hence, provide a promising new tool for the diagnosis of hepatic lipidosis. By generating insights into the molecular pathogenesis of hepatic lipidosis, metabolomics studies may also facilitate the prevention of this syndrome.

  13. Dissemination of metabolomics results: role of MetaboLights and COSMOS.

    PubMed

    Salek, Reza M; Haug, Kenneth; Steinbeck, Christoph

    2013-05-17

    With ever-increasing amounts of metabolomics data produced each year, there is an even greater need to disseminate data and knowledge produced in a standard and reproducible way. To assist with this a general purpose, open source metabolomics repository, MetaboLights, was launched in 2012. To promote a community standard, initially culminated as metabolomics standards initiative (MSI), COordination of Standards in MetabOlomicS (COSMOS) was introduced. COSMOS aims to link life science e-infrastructures within the worldwide metabolomics community as well as develop and maintain open source exchange formats for raw and processed data, ensuring better flow of metabolomics information.

  14. Dissemination of metabolomics results: role of MetaboLights and COSMOS

    PubMed Central

    2013-01-01

    With ever-increasing amounts of metabolomics data produced each year, there is an even greater need to disseminate data and knowledge produced in a standard and reproducible way. To assist with this a general purpose, open source metabolomics repository, MetaboLights, was launched in 2012. To promote a community standard, initially culminated as metabolomics standards initiative (MSI), COordination of Standards in MetabOlomicS (COSMOS) was introduced. COSMOS aims to link life science e-infrastructures within the worldwide metabolomics community as well as develop and maintain open source exchange formats for raw and processed data, ensuring better flow of metabolomics information. PMID:23683662

  15. Application of metabolomics: Focus on the quantification of organic acids in healthy adults

    PubMed Central

    Tsoukalas, Dimitris; Alegakis, Athanasios; Fragkiadaki, Persefoni; Papakonstantinou, Evangelos; Nikitovic, Dragana; Karataraki, Aikaterini; Nosyrev, Alexander E.; Papadakis, Emmanouel G.; Spandidos, Demetrios A.; Drakoulis, Nikolaos; Tsatsakis, Aristides M.

    2017-01-01

    Metabolomics, a 'budding' discipline, may accurately reflect a specific phenotype which is sensitive to genetic and epigenetic interactions. This rapidly evolving field in science has been proposed as a tool for the evaluation of the effects of epigenetic factors, such as nutrition, environment, drug and lifestyle on phenotype. Urine, being sterile, is easy to obtain and as it contains metabolized or non-metabolized products, is a favored study material in the field of metabolomics. Urine organic acids (OAs) reflect the activity of main metabolic pathways and have been used to assess health status, nutritional status, vitamin deficiencies and response to xenobiotics. To date, a limited number of studies have been performed which actually define reference OA values in a healthy population and as reference range for epigenetic influences, and not as a reference to congenital metabolic diseases. The aim of the present study was thus the determination of reference values (RVs) for urine OA in a healthy adult population. Targeted metabolomics analysis of 22 OAs in the urine of 122 healthy adults by gas chromatography-mass spectrometry, was conducted. Percentile distributions of the OA concentrations in urine, as a base for determining the RVs in the respective population sample, were used. No significant differences were detected between female and male individuals. These findings can facilitate the more sensitive determination of OAs in pathological conditions. Therefore, the findings of this study may contribute or add to the information already available on urine metabolite databases, and may thus promote the use of targeted metabolomics for the evaluation of OAs in a clinical setting and for pathophysiological evaluation. However, further studies with well-defined patients groups exhibiting specific symptoms or diseases are warranted in order to discern between normal and pathological values. PMID:28498405

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

    PubMed

    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.

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

    PubMed

    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.

  18. Metabolomics and Personalized Medicine.

    PubMed

    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.

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

    PubMed

    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.

  20. Metabolomics in diabetes, a review.

    PubMed

    Pallares-Méndez, Rigoberto; Aguilar-Salinas, Carlos A; Cruz-Bautista, Ivette; Del Bosque-Plata, Laura

    2016-01-01

    Metabolomics is a promising approach for the identification of chemical compounds that serve for early detection, diagnosis, prediction of therapeutic response and prognosis of disease. Moreover, metabolomics has shown to increase the diagnostic threshold and prediction of type 2 diabetes. Evidence suggests that branched-chain amino acids, acylcarnitines and aromatic amino acids may play an early role on insulin resistance, exposing defects on amino acid metabolism, β-oxidation, and tricarboxylic acid cycle. This review aims to provide a panoramic view of the metabolic shifts that antecede or follow type 2 diabetes. Key messages BCAAs, AAAs and acylcarnitines are strongly associated with early insulin resistance. Diabetes risk prediction has been improved when adding metabolomic markers of dysglycemia to standard clinical and biochemical factors.

  1. Metabolomics applied to the pancreatic islet.

    PubMed

    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.

  2. Applying Metabolomics to differentiate amphibian responses ...

    EPA Pesticide Factsheets

    Introduction/Objectives/Methods One of the biggest challenges in ecological risk assessment is determining the impact of multiple stressors on individual organisms and populations in ‘real world’ scenarios. Emerging ‘omic technologies, notably, metabolomics, provides an opportunity to address the uncertainties surrounding ecological risk assessment of multiple stressors. The objective of this study was to use a metabolomics biomarker approach to investigate the effect of multiple stressors on amphibian metamorphs. To this end, metamorphs of Rana pipiens (northern leopard frogs) were exposed to the insecticide Carbaryl (0.32 μg/L), a conspecific predator alarm call (Lithobates catesbeianus), Carbaryl and the predator alarm call, and a control with no stressor. In addition to metabolomic fingerprinting, we measured corticosterone levels in each treatment to assess general stress response. We analyzed relative abundances of endogenous metabolites collected in liver tissue with gas chromatography coupled with mass spectrometry. Support vector machine (SVM) methods with recursive feature elimination (RFE) were applied to rank the metabolomic profiles produced. Results/Conclusions SVM-RFE of the acquired metabolomic spectra demonstrated 85-96% classification accuracy among control and all treatment groups when using the top 75 ranked retention time bins. Biochemical fluxes observed in the groups exposed to carbaryl, predation threat, and the combined treatmen

  3. Clinical application of metabolomics in neonatology.

    PubMed

    Fanos, Vassilios; Antonucci, Roberto; Barberini, Luigi; Noto, Antonio; Atzori, Luigi

    2012-04-01

    The youngest and more rapidly increasing "omic" discipline, called metabolomics, is the process of describing the phenotype of a cell, tissue or organism through the full complement of metabolites present. Metabolomics measure global sets of low molecular weight metabolites (including amino acids, organic acids, sugars, fatty acids, lipids, steroids, small peptides, vitamins, etc.), thus providing a "snapshot" of the metabolic status of a cell, tissue or organism in relation to genetic variations or external stimuli. The use of metabolomics appears to be a promising tool in neonatology. The management of sick newborns might improve if more information on perinatal/neonatal maturational processes and their metabolic background were available. Urine ("a window on the organism") is a biofluid particularly suitable for metabolomic analysis in neonatology because it may be collected by using simple, noninvasive techniques and because it may provide valuable diagnostic information. In this review, the authors report the few literature data on neonatal metabolomics, including their personal experience, in the following fields: intrauterine growth restriction, perinatal transition, asphyxia, brain injury and hypothermia, maternal milk evaluation, postnatal maturation, bronchiolitis, sepsis, patent ductus arteriosus, respiratory distress syndrome, nephrouropathies, metabolic diseases, antibiotic treatment, perinatal programming and long-term outcome in extremely low birth-weight infants.

  4. Metabolomics and proteomics technologies to explore the herbal preparation affecting metabolic disorders using high resolution mass spectrometry.

    PubMed

    Zhang, Aihua; Zhou, Xiaohang; Zhao, Hongwei; Zou, Shiyu; Ma, Chung Wah; Liu, Qi; Sun, Hui; Liu, Liang; Wang, Xijun

    2017-01-31

    An integrative metabolomics and proteomics approach can provide novel insights in the understanding of biological systems. We have integrated proteome and metabolome data sets for a holistic view of the molecular mechanisms in disease. Using quantitative iTRAQ-LC-MS/MS proteomics coupled with UPLC-Q-TOF-HDMS based metabolomics, we determined the protein and metabolite expression changes in the kidney-yang deficiency syndrome (KYDS) rat model and further investigated the intervention effects of the Jinkui Shenqi Pill (JSP). The VIP-plot of the orthogonal PLS-DA (OPLS-DA) was used for discovering the potential biomarkers to clarify the therapeutic mechanisms of JSP in treating KYDS. The results showed that JSP can alleviate the kidney impairment induced by KYDS. Sixty potential biomarkers, including 5-l-glutamyl-taurine, phenylacetaldehyde, 4,6-dihydroxyquinoline, and xanthurenic acid etc., were definitely up- or down-regulated. The regulatory effect of JSP on the disturbed metabolic pathways was proved by the established metabonomic method. Using pathway analyses, we identified the disturbed metabolic pathways such as taurine and hypotaurine metabolism, pyrimidine metabolism, tyrosine metabolism, tryptophan metabolism, histidine metabolism, steroid hormone biosynthesis, etc. Furthermore, using iTRAQ-based quantitative proteomics analysis, seventeen differential proteins were identified and significantly altered by the JSP treatment. These proteins appear to be involved in Wnt, chemokine, PPAR, and MAPK signaling pathways, etc. Functional pathway analysis revealed that most of the proteins were found to play a key role in the regulation of metabolism pathways. Bioinformatics analysis with the IPA software found that these differentially-expressed moleculars had a strong correlation with the α-adrenergic signaling, FGF signaling, etc. Our data indicate that high-throughput metabolomics and proteomics can provide an insight on the herbal preparations affecting the

  5. Establishing Substantial Equivalence: Metabolomics

    NASA Astrophysics Data System (ADS)

    Beale, Michael H.; Ward, Jane L.; Baker, John M.

    Modern ‘metabolomic’ methods allow us to compare levels of many structurally diverse compounds in an automated fashion across a large number of samples. This technology is ideally suited to screening of populations of plants, including trials where the aim is the determination of unintended effects introduced by GM. A number of metabolomic methods have been devised for the determination of substantial equivalence. We have developed a methodology, using [1H]-NMR fingerprinting, for metabolomic screening of plants and have applied it to the study of substantial equivalence of field-grown GM wheat. We describe here the principles and detail of that protocol as applied to the analysis of flour generated from field plots of wheat. Particular emphasis is given to the downstream data processing and comparison of spectra by multivariate analysis, from which conclusions regarding metabolome changes due to the GM can be assessed against the background of natural variation due to environment.

  6. Target-decoy Based False Discovery Rate Estimation for Large-scale Metabolite Identification.

    PubMed

    Wang, Xusheng; Jones, Drew R; Shaw, Timothy I; Cho, Ji-Hoon; Wang, Yuanyuan; Tan, Haiyan; Xie, Boer; Zhou, Suiping; Li, Yuxin; Peng, Junmin

    2018-05-23

    Metabolite identification is a crucial step in mass spectrometry (MS)-based metabolomics. However, it is still challenging to assess the confidence of assigned metabolites. In this study, we report a novel method for estimating false discovery rate (FDR) of metabolite assignment with a target-decoy strategy, in which the decoys are generated through violating the octet rule of chemistry by adding small odd numbers of hydrogen atoms. The target-decoy strategy was integrated into JUMPm, an automated metabolite identification pipeline for large-scale MS analysis, and was also evaluated with two other metabolomics tools, mzMatch and mzMine 2. The reliability of FDR calculation was examined by false datasets, which were simulated by altering MS1 or MS2 spectra. Finally, we used the JUMPm pipeline coupled with the target-decoy strategy to process unlabeled and stable-isotope labeled metabolomic datasets. The results demonstrate that the target-decoy strategy is a simple and effective method for evaluating the confidence of high-throughput metabolite identification.

  7. Tools for the functional interpretation of metabolomic experiments.

    PubMed

    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.

  8. MetaboLights: towards a new COSMOS of metabolomics data management.

    PubMed

    Steinbeck, Christoph; Conesa, Pablo; Haug, Kenneth; Mahendraker, Tejasvi; Williams, Mark; Maguire, Eamonn; Rocca-Serra, Philippe; Sansone, Susanna-Assunta; Salek, Reza M; Griffin, Julian L

    2012-10-01

    Exciting funding initiatives are emerging in Europe and the US for metabolomics data production, storage, dissemination and analysis. This is based on a rich ecosystem of resources around the world, which has been build during the past ten years, including but not limited to resources such as MassBank in Japan and the Human Metabolome Database in Canada. Now, the European Bioinformatics Institute has launched MetaboLights, a database for metabolomics experiments and the associated metadata (http://www.ebi.ac.uk/metabolights). It is the first comprehensive, cross-species, cross-platform metabolomics database maintained by one of the major open access data providers in molecular biology. In October, the European COSMOS consortium will start its work on Metabolomics data standardization, publication and dissemination workflows. The NIH in the US is establishing 6-8 metabolomics services cores as well as a national metabolomics repository. This communication reports about MetaboLights as a new resource for Metabolomics research, summarises the related developments and outlines how they may consolidate the knowledge management in this third large omics field next to proteomics and genomics.

  9. Assessment of data pre-processing methods for LC-MS/MS-based metabolomics of uterine cervix cancer.

    PubMed

    Chen, Yanhua; Xu, Jing; Zhang, Ruiping; Shen, Guoqing; Song, Yongmei; Sun, Jianghao; He, Jiuming; Zhan, Qimin; Abliz, Zeper

    2013-05-07

    A metabolomics strategy based on rapid resolution liquid chromatography/tandem mass spectrometry (RRLC-MS/MS) and multivariate statistics has been implemented to identify potential biomarkers in uterine cervix cancer. Due to the importance of the data pre-processing method, three popular software packages have been compared. Then they have been used to acquire respective data matrices from the same LC-MS/MS data. Multivariate statistics was subsequently used to identify significantly changed biomarkers for uterine cervix cancer from the resulting data matrices. The reliabilities of the identified discriminated metabolites have been further validated on the basis of manually extracted data and ROC curves. Nine potential biomarkers have been identified as having a close relationship with uterine cervix cancer. Considering these in combination as a biomarker group, the AUC amounted to 0.997, with a sensitivity of 92.9% and a specificity of 95.6%. The prediction accuracy was 96.6%. Among these potential biomarkers, the amounts of four purine derivatives were greatly decreased, which might be related to a P2 receptor that might lead to a decrease in cell number through apoptosis. Moreover, only two of them were identified simultaneously by all of the pre-processing tools. The results have demonstrated that the data pre-processing method could seriously bias the metabolomics results. Therefore, application of two or more data pre-processing methods would reveal a more comprehensive set of potential biomarkers in non-targeted metabolomics, before a further validation with LC-MS/MS based targeted metabolomics in MRM mode could be conducted.

  10. E-Cigarette Affects the Metabolome of Primary Normal Human Bronchial Epithelial Cells.

    PubMed

    Aug, Argo; Altraja, Siiri; Kilk, Kalle; Porosk, Rando; Soomets, Ursel; Altraja, Alan

    2015-01-01

    E-cigarettes are widely believed to be safer than conventional cigarettes and have been even suggested as aids for smoking cessation. However, while reasonable with some regards, this judgment is not yet supported by adequate biomedical research data. Since bronchial epithelial cells are the immediate target of inhaled toxicants, we hypothesized that exposure to e-cigarettes may affect the metabolome of human bronchial epithelial cells (HBEC) and that the changes are, at least in part, induced by oxidant-driven mechanisms. Therefore, we evaluated the effect of e-cigarette liquid (ECL) on the metabolome of HBEC and examined the potency of antioxidants to protect the cells. We assessed the changes of the intracellular metabolome upon treatment with ECL in comparison of the effect of cigarette smoke condensate (CSC) with mass spectrometry and principal component analysis on air-liquid interface model of normal HBEC. Thereafter, we evaluated the capability of the novel antioxidant tetrapeptide O-methyl-l-tyrosinyl-γ-l-glutamyl-l-cysteinylglycine (UPF1) to attenuate the effect of ECL. ECL caused a significant shift in the metabolome that gradually gained its maximum by the 5th hour and receded by the 7th hour. A second alteration followed at the 13th hour. Treatment with CSC caused a significant initial shift already by the 1st hour. ECL, but not CSC, significantly increased the concentrations of arginine, histidine, and xanthine. ECL, in parallel with CSC, increased the content of adenosine diphosphate and decreased that of three lipid species from the phosphatidylcholine family. UPF1 partially counteracted the ECL-induced deviations, UPF1's maximum effect occurred at the 5th hour. The data support our hypothesis that ECL profoundly alters the metabolome of HBEC in a manner, which is comparable and partially overlapping with the effect of CSC. Hence, our results do not support the concept of harmlessness of e-cigarettes.

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

    PubMed

    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.

  12. Metabolomic Studies of Oral Biofilm, Oral Cancer, and Beyond.

    PubMed

    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.

  13. The mzTab data exchange format: communicating mass-spectrometry-based proteomics and metabolomics experimental results to a wider audience.

    PubMed

    Griss, Johannes; Jones, Andrew R; Sachsenberg, Timo; Walzer, Mathias; Gatto, Laurent; Hartler, Jürgen; Thallinger, Gerhard G; Salek, Reza M; Steinbeck, Christoph; Neuhauser, Nadin; Cox, Jürgen; Neumann, Steffen; Fan, Jun; Reisinger, Florian; Xu, Qing-Wei; Del Toro, Noemi; Pérez-Riverol, Yasset; Ghali, Fawaz; Bandeira, Nuno; Xenarios, Ioannis; Kohlbacher, Oliver; Vizcaíno, Juan Antonio; Hermjakob, Henning

    2014-10-01

    The HUPO Proteomics Standards Initiative has developed several standardized data formats to facilitate data sharing in mass spectrometry (MS)-based proteomics. These allow researchers to report their complete results in a unified way. However, at present, there is no format to describe the final qualitative and quantitative results for proteomics and metabolomics experiments in a simple tabular format. Many downstream analysis use cases are only concerned with the final results of an experiment and require an easily accessible format, compatible with tools such as Microsoft Excel or R. We developed the mzTab file format for MS-based proteomics and metabolomics results to meet this need. mzTab is intended as a lightweight supplement to the existing standard XML-based file formats (mzML, mzIdentML, mzQuantML), providing a comprehensive summary, similar in concept to the supplemental material of a scientific publication. mzTab files can contain protein, peptide, and small molecule identifications together with experimental metadata and basic quantitative information. The format is not intended to store the complete experimental evidence but provides mechanisms to report results at different levels of detail. These range from a simple summary of the final results to a representation of the results including the experimental design. This format is ideally suited to make MS-based proteomics and metabolomics results available to a wider biological community outside the field of MS. Several software tools for proteomics and metabolomics have already adapted the format as an output format. The comprehensive mzTab specification document and extensive additional documentation can be found online. © 2014 by The American Society for Biochemistry and Molecular Biology, Inc.

  14. Present and foreseeable future of metabolomics in forensic analysis.

    PubMed

    Castillo-Peinado, L S; Luque de Castro, M D

    2016-06-21

    The revulsive publications during the last years on the precariousness of forensic sciences worldwide have promoted the move of major steps towards improvement of this science. One of the steps (viz. a higher involvement of metabolomics in the new era of forensic analysis) deserves to be discussed under different angles. Thus, the characteristics of metabolomics that make it a useful tool in forensic analysis, the aspects in which this omics is so far implicit, but not mentioned in forensic analyses, and how typical forensic parameters such as the post-mortem interval or fingerprints take benefits from metabolomics are critically discussed in this review. The way in which the metabolomics-forensic binomial succeeds when either conventional or less frequent samples are used is highlighted here. Finally, the pillars that should support future developments involving metabolomics and forensic analysis, and the research required for a fruitful in-depth involvement of metabolomics in forensic analysis are critically discussed. Copyright © 2016 Elsevier B.V. All rights reserved.

  15. Metabolome and proteome profiling of complex I deficiency induced by rotenone.

    PubMed

    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.

  16. Metabolomic biomarkers correlating with hepatic lipidosis in dairy cows

    PubMed Central

    2014-01-01

    Background Hepatic lipidosis or fatty liver disease is a major metabolic disorder of high-producing dairy cows that compromises animal performance and, hence, causes heavy economic losses worldwide. This syndrome, occurring during the critical transition from gestation to early lactation, leads to an impaired health status, decreased milk yield, reduced fertility and shortened lifetime. Because the prevailing clinical chemistry parameters indicate advanced liver damage independently of the underlying disease, currently, hepatic lipidosis can only be ascertained by liver biopsy. We hypothesized that the condition of fatty liver disease may be accompanied by an altered profile of endogenous metabolites in the blood of affected animals. Results To identify potential small-molecule biomarkers as a novel diagnostic alternative, the serum samples of diseased dairy cows were subjected to a targeted metabolomics screen by triple quadrupole mass spectrometry. A subsequent multivariate test involving principal component and linear discriminant analyses yielded 29 metabolites (amino acids, phosphatidylcholines and sphingomyelines) that, in conjunction, were able to distinguish between dairy cows with no hepatic lipidosis and those displaying different stages of the disorder. Conclusions This proof-of-concept study indicates that metabolomic profiles, including both amino acids and lipids, distinguish hepatic lipidosis from other peripartal disorders and, hence, provide a promising new tool for the diagnosis of hepatic lipidosis. By generating insights into the molecular pathogenesis of hepatic lipidosis, metabolomics studies may also facilitate the prevention of this syndrome. PMID:24888604

  17. Metabolomics analysis reveals elevation of 3-indoxyl sulfate in plasma and brain during chemically-induced acute kidney injury in mice: Investigation of nicotinic acid receptor agonists

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Zgoda-Pols, Joanna R., E-mail: joanna.pols@merck.com; Chowdhury, Swapan; Wirth, Mark

    2011-08-15

    An investigative renal toxicity study using metabolomics was conducted with a potent nicotinic acid receptor (NAR) agonist, SCH 900424. Liquid chromatography-mass spectrometry (LC-MS) and gas chromatography-mass spectrometry (GC-MS) techniques were used to identify small molecule biomarkers of acute kidney injury (AKI) that could aid in a better mechanistic understanding of SCH 900424-induced AKI in mice. The metabolomics study revealed 3-indoxyl sulfate (3IS) as a more sensitive marker of SCH 900424-induced renal toxicity than creatinine or urea. An LC-MS assay for quantitative determination of 3IS in mouse matrices was also developed. Following treatment with SCH 900424, 3IS levels were markedly increasedmore » in murine plasma and brain, thereby potentially contributing to renal- and central nervous system (CNS)-related rapid onset of toxicities. Furthermore, significant decrease in urinary excretion of 3IS in those animals due to compromised renal function may be associated with the elevation of 3IS in plasma and brain. These data suggest that 3IS has a potential to be a marker of renal and CNS toxicities during chemically-induced AKI in mice. In addition, based on the metabolomic analysis other statistically significant plasma markers including p-cresol-sulfate and tryptophan catabolites (kynurenate, kynurenine, 3-indole-lactate) might be of toxicological importance but have not been studied in detail. This comprehensive approach that includes untargeted metabolomic and targeted bioanalytical sample analyses could be used to investigate toxicity of other compounds that pose preclinical or clinical development challenges in a pharmaceutical discovery and development. - Research Highlights: > Nicotinic acid receptor agonist, SCH 900424, caused acute kidney injury in mice. > MS-based metabolomics was conducted to identify potential small molecule markers of renal toxicity. > 3-indoxyl-sulfate was found to be as a more sensitive marker of renal toxicity than

  18. Challenges of metabolomics in human gut microbiota research.

    PubMed

    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.

  19. Brain Injury Alters Volatile Metabolome

    PubMed Central

    Cohen, Akiva S.; Gordon, Amy R.; Opiekun, Maryanne; Martin, Talia; Elkind, Jaclynn; Lundström, Johan N.; Beauchamp, Gary K.

    2016-01-01

    Chemical signals arising from body secretions and excretions communicate information about health status as have been reported in a range of animal models of disease. A potential common pathway for diseases to alter chemical signals is via activation of immune function—which is known to be intimately involved in modulation of chemical signals in several species. Based on our prior findings that both immunization and inflammation alter volatile body odors, we hypothesized that injury accompanied by inflammation might correspondingly modify the volatile metabolome to create a signature endophenotype. In particular, we investigated alteration of the volatile metabolome as a result of traumatic brain injury. Here, we demonstrate that mice could be trained in a behavioral assay to discriminate mouse models subjected to lateral fluid percussion injury from appropriate surgical sham controls on the basis of volatile urinary metabolites. Chemical analyses of the urine samples similarly demonstrated that brain injury altered urine volatile profiles. Behavioral and chemical analyses further indicated that alteration of the volatile metabolome induced by brain injury and alteration resulting from lipopolysaccharide-associated inflammation were not synonymous. Monitoring of alterations in the volatile metabolome may be a useful tool for rapid brain trauma diagnosis and for monitoring recovery. PMID:26926034

  20. Metabolomics and Its Application to Acute Lung Diseases

    PubMed Central

    Stringer, Kathleen A.; McKay, Ryan T.; Karnovsky, Alla; Quémerais, Bernadette; Lacy, Paige

    2016-01-01

    Metabolomics is a rapidly expanding field of systems biology that is gaining significant attention in many areas of biomedical research. Also known as metabonomics, it comprises the analysis of all small molecules or metabolites that are present within an organism or a specific compartment of the body. Metabolite detection and quantification provide a valuable addition to genomics and proteomics and give unique insights into metabolic changes that occur in tangent to alterations in gene and protein activity that are associated with disease. As a novel approach to understanding disease, metabolomics provides a “snapshot” in time of all metabolites present in a biological sample such as whole blood, plasma, serum, urine, and many other specimens that may be obtained from either patients or experimental models. In this article, we review the burgeoning field of metabolomics in its application to acute lung diseases, specifically pneumonia and acute respiratory disease syndrome (ARDS). We also discuss the potential applications of metabolomics for monitoring exposure to aerosolized environmental toxins. Recent reports have suggested that metabolomics analysis using nuclear magnetic resonance (NMR) and mass spectrometry (MS) approaches may provide clinicians with the opportunity to identify new biomarkers that may predict progression to more severe disease, such as sepsis, which kills many patients each year. In addition, metabolomics may provide more detailed phenotyping of patient heterogeneity, which is needed to achieve the goal of precision medicine. However, although several experimental and clinical metabolomics studies have been conducted assessing the application of the science to acute lung diseases, only incremental progress has been made. Specifically, little is known about the metabolic phenotypes of these illnesses. These data are needed to substantiate metabolomics biomarker credentials so that clinicians can employ them for clinical decision

  1. Reprogramming the metabolome rescues retinal degeneration.

    PubMed

    Park, Karen Sophia; Xu, Christine L; Cui, Xuan; Tsang, Stephen H

    2018-05-01

    Metabolomics studies in the context of ophthalmology have largely focused on identifying metabolite concentrations that characterize specific retinal diseases. Studies involving mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy have shown that individuals suffering from retinal diseases exhibit metabolic profiles that markedly differ from those of control individuals, supporting the notion that metabolites may serve as easily identifiable biomarkers for specific conditions. An emerging branch of metabolomics resulting from biomarker studies, however, involves the study of retinal metabolic dysfunction as causes of degeneration. Recent publications have identified a number of metabolic processes-including but not limited to glucose and oxygen metabolism-that, when perturbed, play a role in the degeneration of photoreceptor cells. As a result, such studies have led to further research elucidating methods for prolonging photoreceptor survival in an effort to halt degeneration in its early stages. This review will explore the ways in which metabolomics has deepened our understanding of the causes of retinal degeneration and discuss how metabolomics can be used to prevent retinal degeneration from progressing to its later disease stages.

  2. Quantitative metabolome analysis profiles activation of glutaminolysis in glioma with IDH1 mutation.

    PubMed

    Ohka, Fumiharu; Ito, Maki; Ranjit, Melissa; Senga, Takeshi; Motomura, Ayako; Motomura, Kazuya; Saito, Kaori; Kato, Keiko; Kato, Yukinari; Wakabayashi, Toshihiko; Soga, Tomoyoshi; Natsume, Atsushi

    2014-06-01

    Isocitrate dehydrogenase 1 (IDH1), which localizes to the cytosol and peroxisomes, catalyzes the oxidative decarboxylation of isocitrate to α-ketoglutarate (α-KG) and in parallel converts NADP(+) to NADPH. IDH1 mutations are frequently detected in grades 2-4 gliomas and in acute myeloid leukemias (AML). Mutations of IDH1 have been identified at codon 132, with arginine being replaced with histidine in most cases. Mutant IDH1 gains novel enzyme activity converting α-KG to D-2-hydroxyglutarate (2-HG) which acts as a competitive inhibitor of α-KG. As a result, the activity of α-KG-dependent enzyme is reduced. Based on these findings, 2-HG has been proposed to be an oncometabolite. In this study, we established HEK293 and U87 cells that stably expressed IDH1-WT and IDH1-R132H and investigated the effect of glutaminase inhibition on cell proliferation with 6-diazo-5-oxo-L-norleucine (DON). We found that cell proliferation was suppressed in IDH1-R132H cells. The addition of α-KG restored cell proliferation. The metabolic features of 33 gliomas with wild type IDH1 (IDH1-WT) and with IDH1-R132H mutation were examined by global metabolome analysis using capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS). We showed that the 2-HG levels were highly elevated in gliomas with IDH1-R132H mutation. Intriguingly, in gliomas with IDH1-R132H, glutamine and glutamate levels were significantly reduced which implies replenishment of α-KG by glutaminolysis. Based on these results, we concluded that glutaminolysis is activated in gliomas with IDH1-R132H mutation and that development of novel therapeutic approaches targeting activated glutaminolysis is warranted.

  3. Metabolomics Coupled with Multivariate Data and Pathway Analysis on Potential Biomarkers in Gastric Ulcer and Intervention Effects of Corydalis yanhusuo Alkaloid

    PubMed Central

    Shuai, Wang; Yongrui, Bao; Shanshan, Guan; Bo, Liu; Lu, Chen; Lei, Wang; Xiaorong, Ran

    2014-01-01

    Metabolomics, the systematic analysis of potential metabolites in a biological specimen, has been increasingly applied to discovering biomarkers, identifying perturbed pathways, measuring therapeutic targets, and discovering new drugs. By analyzing and verifying the significant difference in metabolic profiles and changes of metabolite biomarkers, metabolomics enables us to better understand substance metabolic pathways which can clarify the mechanism of Traditional Chinese Medicines (TCM). Corydalis yanhusuo alkaloid (CA) is a major component of Qizhiweitong (QZWT) prescription which has been used for treating gastric ulcer for centuries and its mechanism remains unclear completely. Metabolite profiling was performed by high-performance liquid chromatography combined with time-of-flight mass spectrometry (HPLC/ESI-TOF-MS) and in conjunction with multivariate data analysis and pathway analysis. The statistic software Mass Profiller Prossional (MPP) and statistic method including ANOVA and principal component analysis (PCA) were used for discovering novel potential biomarkers to clarify mechanism of CA in treating acid injected rats with gastric ulcer. The changes in metabolic profiling were restored to their base-line values after CA treatment according to the PCA score plots. Ten different potential biomarkers and seven key metabolic pathways contributing to the treatment of gastric ulcer were discovered and identified. Among the pathways, sphingophospholipid metabolism and fatty acid metabolism related network were acutely perturbed. Quantitative real time polymerase chain reaction (RT-PCR) analysis were performed to evaluate the expression of genes related to the two pathways for verifying the above results. The results show that changed biomarkers and pathways may provide evidence to insight into drug action mechanisms and enable us to increase research productivity toward metabolomics drug discovery. PMID:24454691

  4. Metabolomic Studies of Oral Biofilm, Oral Cancer, and Beyond

    PubMed Central

    Washio, Jumpei; Takahashi, Nobuhiro

    2016-01-01

    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. PMID:27271597

  5. Relationships between drought, heat and air humidity responses revealed by transcriptome-metabolome co-analysis.

    PubMed

    Georgii, Elisabeth; Jin, Ming; Zhao, Jin; Kanawati, Basem; Schmitt-Kopplin, Philippe; Albert, Andreas; Winkler, J Barbro; Schäffner, Anton R

    2017-07-10

    Elevated temperature and reduced water availability are frequently linked abiotic stresses that may provoke distinct as well as interacting molecular responses. Based on non-targeted metabolomic and transcriptomic measurements from Arabidopsis rosettes, this study aims at a systematic elucidation of relevant components in different drought and heat scenarios as well as relationships between molecular players of stress response. In combined drought-heat stress, the majority of single stress responses are maintained. However, interaction effects between drought and heat can be discovered as well; these relate to protein folding, flavonoid biosynthesis and growth inhibition, which are enhanced, reduced or specifically induced in combined stress, respectively. Heat stress experiments with and without supplementation of air humidity for maintenance of vapor pressure deficit suggest that decreased relative air humidity due to elevated temperature is an important component of heat stress, specifically being responsible for hormone-related responses to water deprivation. Remarkably, this "dry air effect" is the primary trigger of the metabolomic response to heat. In contrast, the transcriptomic response has a substantial temperature component exceeding the dry air component and including up-regulation of many transcription factors and protein folding-related genes. Data level integration independent of prior knowledge on pathways and condition labels reveals shared drought and heat responses between transcriptome and metabolome, biomarker candidates and co-regulation between genes and metabolic compounds, suggesting novel players in abiotic stress response pathways. Drought and heat stress interact both at transcript and at metabolite response level. A comprehensive, non-targeted view of this interaction as well as non-interacting processes is important to be taken into account when improving tolerance to abiotic stresses in breeding programs. Transcriptome and metabolome

  6. Random sample consensus combined with partial least squares regression (RANSAC-PLS) for microbial metabolomics data mining and phenotype improvement.

    PubMed

    Teoh, Shao Thing; Kitamura, Miki; Nakayama, Yasumune; Putri, Sastia; Mukai, Yukio; Fukusaki, Eiichiro

    2016-08-01

    In recent years, the advent of high-throughput omics technology has made possible a new class of strain engineering approaches, based on identification of possible gene targets for phenotype improvement from omic-level comparison of different strains or growth conditions. Metabolomics, with its focus on the omic level closest to the phenotype, lends itself naturally to this semi-rational methodology. When a quantitative phenotype such as growth rate under stress is considered, regression modeling using multivariate techniques such as partial least squares (PLS) is often used to identify metabolites correlated with the target phenotype. However, linear modeling techniques such as PLS require a consistent metabolite-phenotype trend across the samples, which may not be the case when outliers or multiple conflicting trends are present in the data. To address this, we proposed a data-mining strategy that utilizes random sample consensus (RANSAC) to select subsets of samples with consistent trends for construction of better regression models. By applying a combination of RANSAC and PLS (RANSAC-PLS) to a dataset from a previous study (gas chromatography/mass spectrometry metabolomics data and 1-butanol tolerance of 19 yeast mutant strains), new metabolites were indicated to be correlated with tolerance within certain subsets of the samples. The relevance of these metabolites to 1-butanol tolerance were then validated from single-deletion strains of corresponding metabolic genes. The results showed that RANSAC-PLS is a promising strategy to identify unique metabolites that provide additional hints for phenotype improvement, which could not be detected by traditional PLS modeling using the entire dataset. Copyright © 2016 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

  7. The Nutritional Phenotype in the Age of Metabolomics

    PubMed Central

    Zeisel, S. H.; Freake, H. C.; Bauman, D. E.; Bier, D. M.; Burrin, D. G.; German, J. B.; Klein, S.; Marquis, G. S.; Milner, J. A.; Pelto, G. H.; Rasmussen, K. M.

    2008-01-01

    The concept of the nutritional phenotype is proposed as a defined and integrated set of genetic, proteomic, metabolomic, functional, and behavioral factors that, when measured, form the basis for assessment of human nutritional status. The nutritional phenotype integrates the effects of diet on disease/wellness and is the quantitative indication of the paths by which genes and environment exert their effects on health. Advances in technology and in fundamental biological knowledge make it possible to define and measure the nutritional phenotype accurately in a cross section of individuals with various states of health and disease. This growing base of data and knowledge could serve as a resource for all scientific disciplines involved in human health. Nutritional sciences should be a prime mover in making key decisions that include: what environmental inputs (in addition to diet) are needed; what genes/proteins/metabolites should be measured; what end-point phenotypes should be included; and what informatics tools are available to ask nutritionally relevant questions. Nutrition should be the major discipline establishing how the elements of the nutritional phenotype vary as a function of diet. Nutritional sciences should also be instrumental in linking the elements that are responsive to diet with the functional outcomes in organisms that derive from them. As the first step in this initiative, a prioritized list of genomic, proteomic, and metabolomic as well as functional and behavioral measures that defines a practically useful subset of the nutritional phenotype for use in clinical and epidemiological investigations must be developed. From this list, analytic platforms must then be identified that are capable of delivering highly quantitative data on these endpoints. This conceptualization of a nutritional phenotype provides a concrete form and substance to the recognized future of nutritional sciences as a field addressing diet, integrated metabolism, and health

  8. Compliance with minimum information guidelines in public metabolomics repositories

    PubMed Central

    Spicer, Rachel A.; Salek, Reza; Steinbeck, Christoph

    2017-01-01

    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. PMID:28949328

  9. Compliance with minimum information guidelines in public metabolomics repositories.

    PubMed

    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.

  10. Cerebrospinal Fluid Metabolomics After Natural Product Treatment in an Experimental Model of Cerebral Ischemia.

    PubMed

    Huan, Tao; Xian, Jia Wen; Leung, Wing Nang; Li, Liang; Chan, Chun Wai

    2016-11-01

    Cerebrospinal fluid (CSF) is an important biofluid for diagnosis of and research on neurological diseases. However, in-depth metabolomic profiling of CSF remains an analytical challenge due to the small volume of samples, particularly in small animal models. In this work, we report the application of a high-performance chemical isotope labeling (CIL) liquid chromatography-mass spectrometry (LC-MS) workflow for CSF metabolomics in Gastrodia elata and Uncaria rhynchophylla water extract (GUW)-treated experimental cerebral ischemia model of rat. The GUW is a commonly used Traditional Chinese Medicine (TCM) for hypertension and brain disease. This study investigated the amine- and phenol-containing biomarkers in the CSF metabolome. After GUW treatment for 7 days, the neurological deficit score was significantly improved with infarct volume reduction, while the integrity of brain histological structure was preserved. Over 1957 metabolites were quantified in CSF by dansylation LC-MS. The analysis of this comprehensive list of metabolites suggests that metabolites associated with oxidative stress, inflammatory response, and excitotoxicity change during GUW-induced alleviation of ischemic injury. This work is significant in that (1) it shows CIL LC-MS can be used for in-depth profiling of the CSF metabolome in experimental ischemic stroke and (2) identifies several potential molecular targets (that might mediate the central nervous system) and associate with pharmacodynamic effects of some frequently used TCMs.

  11. Metabolomics in transfusion medicine.

    PubMed

    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.

  12. Ultrasound: a subexploited tool for sample preparation in metabolomics.

    PubMed

    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.

  13. An emerging strategy for evaluating the grades of Keemun black tea by combinatory liquid chromatography-Orbitrap mass spectrometry-based untargeted metabolomics and inhibition effects on α-glucosidase and α-amylase.

    PubMed

    Guo, Xuemei; Long, Piaopiao; Meng, Qilu; Ho, Chi-Tang; Zhang, Liang

    2018-04-25

    Quantitative analysis and untargeted liquid chromatography mass spectrum (LC-MS) based metabolomics of different grades of Keemun black tea (KBT) were conducted. Quantitative analysis did not show tight correlation between tea grades and contents of polyphenols, but untargeted metabolomics analysis revealed that high-grades KBT were distinguished from the low-grades. S-plot and Variable Importance (VIP) analysis gave 28 marker compounds responsible for the discrimination of different grades of KBT. The inhibitory effects of KBT on α-amylase and α-glucosidase were positively correlated to tea grades, and the correlation coefficient between each marker compound and inhibitory rate were calculated. Thirteen compounds were positively related to the anti-glycemic activity, and theasinensin A, afzelechin gallate and kaempferol-glucoside were confirmed as grade-related bioactive marker compounds by chemical and bioassay in effective fractions. This study suggested that combinatory metabolomics and bioactivities assay provided a new strategy for the classification of tea grades. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

    PubMed

    McCloskey, Douglas; Xu, Julia; Schrübbers, Lars; Christensen, Hanne B; Herrgård, Markus J

    2018-04-25

    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 that was capable of quantifying 102 metabolites from central, amino acid, energy, nucleotide, and cofactor metabolism in less than 5 minutes. The method was shown to have comparable sensitivity and resolving capability as compared to a full length RIP-LC-MS/MS method (FullRIP). The RapidRIP method was used 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 of biochemical reactions between strains that could have implications when choosing a host for bioprocessing. Copyright © 2018. Published by Elsevier Inc.

  15. Enzymatically Modified Starch Ameliorates Postprandial Serum Triglycerides and Lipid Metabolome in Growing Pigs.

    PubMed

    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 (P<0.05) immediate serum insulin and plasma glucose response compared to pigs fed the control diet; however, area-under-the-curves for insulin and glucose were not different among diets. Results from MTT indicated reduced postprandial serum triglycerides with EMS versus control diet (P<0.05). Likewise, serum metabolome 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

  16. Enzymatically Modified Starch Ameliorates Postprandial Serum Triglycerides and Lipid Metabolome in Growing Pigs

    PubMed Central

    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 (P<0.05) immediate serum insulin and plasma glucose response compared to pigs fed the control diet; however, area-under-the-curves for insulin and glucose were not different among diets. Results from MTT indicated reduced postprandial serum triglycerides with EMS versus control diet (P<0.05). Likewise, serum metabolome 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

  17. Quantitative targeting maps based on experimental investigations for a branched tube model in magnetic drug targeting

    NASA Astrophysics Data System (ADS)

    Gitter, K.; Odenbach, S.

    2011-12-01

    Magnetic drug targeting (MDT), because of its high targeting efficiency, is a promising approach for tumour treatment. Unwanted side effects are considerably reduced, since the nanoparticles are concentrated within the target region due to the influence of a magnetic field. Nevertheless, understanding the transport phenomena of nanoparticles in an artery system is still challenging. This work presents experimental results for a branched tube model. Quantitative results describe, for example, the net amount of nanoparticles that are targeted towards the chosen region due to the influence of a magnetic field. As a result of measurements, novel drug targeting maps, combining, e.g. the magnetic volume force, the position of the magnet and the net amount of targeted nanoparticles, are presented. The targeting maps are valuable for evaluation and comparison of setups and are also helpful for the design and the optimisation of a magnet system with an appropriate strength and distribution of the field gradient. The maps indicate the danger of accretion within the tube and also show the promising result of magnetic drug targeting that up to 97% of the nanoparticles were successfully targeted.

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

    PubMed

    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.

  19. Told through the wine: A liquid chromatography-mass spectrometry interplatform comparison reveals the influence of the global approach on the final annotated metabolites in non-targeted metabolomics.

    PubMed

    Díaz, Ramon; Gallart-Ayala, Hector; Sancho, Juan V; Nuñez, Oscar; Zamora, Tatiana; Martins, Claudia P B; Hernández, Félix; Hernández-Cassou, Santiago; Saurina, Javier; Checa, Antonio

    2016-02-12

    This work focuses on the influence of the selected LC-HRMS platform on the final annotated compounds in non-targeted metabolomics. Two platforms that differed in columns, mobile phases, gradients, chromatographs, mass spectrometers (Orbitrap [Platform#1] and Q-TOF [Platform#2]), data processing and marker selection protocols were compared. A total of 42 wines samples from three different protected denomination of origin (PDO) were analyzed. At the feature level, good (O)PLS-DA models were obtained for both platforms (Q(2)[Platform#1]=0.89, 0.83 and 0.72; Q(2)[Platform#2]=0.86, 0.86 and 0.77 for Penedes, Ribera del Duero and Rioja wines respectively) with 100% correctly classified samples in all cases. At the annotated metabolite level, platforms proposed 9 and 8 annotated metabolites respectively which were identified by matching standards or the MS/MS spectra of the compounds. At this stage, there was no coincidence among platforms regarding the suggested metabolites. When screened on the raw data, 6 and 5 of these compounds were detected on the other platform with a similar trend. Some of the detected metabolites showed complimentary information when integrated on biological pathways. Through the use of some examples at the annotated metabolite level, possible explanations of this initial divergence on the results are presented. This work shows the complications that may arise on the comparison of non-targeted metabolomics platforms even when metabolite focused approaches are used in the identification. Copyright © 2016 Elsevier B.V. All rights reserved.

  20. 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.

    PubMed

    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.

  1. Associations Between the Serum Metabolome and All-Cause Mortality Among African Americans in the Atherosclerosis Risk in Communities (ARIC) Study

    PubMed Central

    Yu, Bing; Heiss, Gerardo; Alexander, Danny; Grams, Morgan E.; Boerwinkle, Eric

    2016-01-01

    Early and accurate identification of people at high risk of premature death may assist in the targeting of preventive therapies in order to improve overall health. To identify novel biomarkers for all-cause mortality, we performed untargeted metabolomics in the Atherosclerosis Risk in Communities (ARIC) Study. We included 1,887 eligible ARIC African Americans, and 671 deaths occurred during a median follow-up period of 22.5 years (1987–2011). Chromatography and mass spectroscopy identified and quantitated 204 serum metabolites, and Cox proportional hazards models were used to analyze the longitudinal associations with all-cause and cardiovascular mortality. Nine metabolites, including cotinine, mannose, glycocholate, pregnendiol disulfate, α-hydroxyisovalerate, N-acetylalanine, andro-steroid monosulfate 2, uridine, and γ-glutamyl-leucine, showed independent associations with all-cause mortality, with an average risk change of 18% per standard-deviation increase in metabolite level (P < 1.23 × 10−4). A metabolite risk score, created on the basis of the weighted levels of the identified metabolites, improved the predictive ability of all-cause mortality over traditional risk factors (bias-corrected Harrell's C statistic 0.752 vs. 0.730). Mannose and glycocholate were associated with cardiovascular mortality (P < 1.23 × 10−4), but predictive ability was not improved beyond the traditional risk factors. This metabolomic analysis revealed potential novel biomarkers for all-cause mortality beyond the traditional risk factors. PMID:26956554

  2. LC-MS data processing with MAVEN: a metabolomic analysis and visualization engine.

    PubMed

    Clasquin, Michelle F; Melamud, Eugene; Rabinowitz, Joshua D

    2012-03-01

    MAVEN is an open-source software program for interactive processing of LC-MS-based metabolomics data. MAVEN enables rapid and reliable metabolite quantitation from multiple reaction monitoring data or high-resolution full-scan mass spectrometry data. It automatically detects and reports peak intensities for isotope-labeled metabolites. Menu-driven, click-based navigation allows visualization of raw and analyzed data. Here we provide a User Guide for MAVEN. Step-by-step instructions are provided for data import, peak alignment across samples, identification of metabolites that differ strongly between biological conditions, quantitation and visualization of isotope-labeling patterns, and export of tables of metabolite-specific peak intensities. Together, these instructions describe a workflow that allows efficient processing of raw LC-MS data into a form ready for biological analysis.

  3. Combination of Metabolomics with Cellular Assays Reveals New Biomarkers and Mechanistic Insights on Xenoestrogenic Exposures in MCF-7 Cells.

    PubMed

    Potratz, Sarah; Tarnow, Patrick; Jungnickel, Harald; Baumann, Sven; von Bergen, Martin; Tralau, Tewes; Luch, Andreas

    2017-04-17

    The disruptive potential of xenoestrogens like bisphenol A (BPA) lies in their 17β-estradiol (E2)-like binding to estrogen receptors (ERs) followed by concomitant modulation of ER target gene expression. Unsurprisingly, most endocrine testing systems focus on the quantification of canonical transcripts or ER-sensitive reporters. However, only little information is available about the corresponding metabolomic changes in vitro. This knowledge gap becomes particularly relevant in the context of potential mixture effects, for example, as a consequence of coexposure to potentially estrogenically active pollutants (e.g., Cd 2+ ). Such effects are often difficult to dissect with molecular tools, especially with regard to potential physiological relevance. Metabolomic biomarkers are well-suited to address this latter aspect as they provide a comprehensive readout of whole-cell physiology. Applying a targeted metabolomics approach (FIA-MS/MS), this study looked for biomarkers indicative of xenoestrogenic exposure in MCF-7 cells. Cells were treated with E2 and BPA in the presence or absence of Cd 2+ . Statistical analysis revealed a total of 11 amino acids and phospholipids to be related to the compound's estrogenic potency. Co-exposure to Cd 2+ modulated the estrogenic profile. However, the corresponding changes were found to be moderate with cellular assays such as the E-screen failing to record any Cd 2+ -specific estrogenic effects. Overall, metabolomics analysis identified proline as the most prominent estrogenic biomarker. Its increase could clearly be related to estrogenic exposure and concomitant ERα-mediated induction of proliferation. Involvement of the latter was confirmed by siRNA-mediated knockdown studies as well as by receptor inhibition. Further, the underlying signaling was also found to involve the oncoprotein MYC. Taken together, this study provides insights into the underlying mechanisms of xenoestrogenic effects and exemplify the strength of the

  4. Dynamic metabolome profiling reveals significant metabolic changes during grain development of bread wheat (Triticum aestivum L.).

    PubMed

    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.

  5. MVAPACK: A Complete Data Handling Package for NMR Metabolomics

    PubMed Central

    2015-01-01

    Data handling in the field of NMR metabolomics has historically been reliant on either in-house mathematical routines or long chains of expensive commercial software. Thus, while the relatively simple biochemical protocols of metabolomics maintain a low barrier to entry, new practitioners of metabolomics experiments are forced to either purchase expensive software packages or craft their own data handling solutions from scratch. This inevitably complicates the standardization and communication of data handling protocols in the field. We report a newly developed open-source platform for complete NMR metabolomics data handling, MVAPACK, and describe its application on an example metabolic fingerprinting data set. PMID:24576144

  6. Impact of a cafeteria diet and daily physical training on the rat serum metabolome

    PubMed Central

    Suárez-García, Susana; del Bas, Josep M.; Caimari, Antoni; Escorihuela, Rosa M.; Arola, Lluís; Suárez, Manuel

    2017-01-01

    Regular physical activity and healthy dietary patterns are commonly recommended for the prevention and treatment of metabolic syndrome (MetS), which is diagnosed at an alarmingly increasing rate, especially among adolescents. Nevertheless, little is known regarding the relevance of physical exercise on the modulation of the metabolome in healthy people and those with MetS. We have previously shown that treadmill exercise ameliorated different symptoms of MetS. The aim of this study was to investigate the impact of a MetS-inducing diet and different intensities of aerobic training on the overall serum metabolome of adolescent rats. For 8 weeks, young rats were fed either standard chow (ST) or cafeteria diet (CAF) and were subjected to a daily program of training on a treadmill at different speeds. Non-targeted metabolomics was used to identify changes in circulating metabolites, and a combination of multivariate analysis techniques was implemented to achieve a holistic understanding of the metabolome. Among all the identified circulating metabolites influenced by CAF, lysophosphatidylcholines were the most represented family. Serum sphingolipids, bile acids, acylcarnitines, unsaturated fatty acids and vitamin E and A derivatives also changed significantly in CAF-fed rats. These findings suggest that an enduring systemic inflammatory state is induced by CAF. The impact of physical training on the metabolome was less striking than the impact of diet and mainly altered circulating bile acids and glycerophospholipids. Furthermore, the serum levels of monocyte chemoattractant protein-1 were increased in CAF-fed rats, and C-reactive protein was decreased in trained groups. The leptin/adiponectin ratio, a useful marker of MetS, was increased in CAF groups, but decreased in proportion to training intensity. Multivariate analysis revealed that ST-fed animals were more susceptible to exercise-induced changes in metabolites than animals with MetS, in which moderate

  7. Impact of a cafeteria diet and daily physical training on the rat serum metabolome.

    PubMed

    Suárez-García, Susana; Del Bas, Josep M; Caimari, Antoni; Escorihuela, Rosa M; Arola, Lluís; Suárez, Manuel

    2017-01-01

    Regular physical activity and healthy dietary patterns are commonly recommended for the prevention and treatment of metabolic syndrome (MetS), which is diagnosed at an alarmingly increasing rate, especially among adolescents. Nevertheless, little is known regarding the relevance of physical exercise on the modulation of the metabolome in healthy people and those with MetS. We have previously shown that treadmill exercise ameliorated different symptoms of MetS. The aim of this study was to investigate the impact of a MetS-inducing diet and different intensities of aerobic training on the overall serum metabolome of adolescent rats. For 8 weeks, young rats were fed either standard chow (ST) or cafeteria diet (CAF) and were subjected to a daily program of training on a treadmill at different speeds. Non-targeted metabolomics was used to identify changes in circulating metabolites, and a combination of multivariate analysis techniques was implemented to achieve a holistic understanding of the metabolome. Among all the identified circulating metabolites influenced by CAF, lysophosphatidylcholines were the most represented family. Serum sphingolipids, bile acids, acylcarnitines, unsaturated fatty acids and vitamin E and A derivatives also changed significantly in CAF-fed rats. These findings suggest that an enduring systemic inflammatory state is induced by CAF. The impact of physical training on the metabolome was less striking than the impact of diet and mainly altered circulating bile acids and glycerophospholipids. Furthermore, the serum levels of monocyte chemoattractant protein-1 were increased in CAF-fed rats, and C-reactive protein was decreased in trained groups. The leptin/adiponectin ratio, a useful marker of MetS, was increased in CAF groups, but decreased in proportion to training intensity. Multivariate analysis revealed that ST-fed animals were more susceptible to exercise-induced changes in metabolites than animals with MetS, in which moderate

  8. Working Up a Good Sweat – The Challenges of Standardising Sweat Collection for Metabolomics Analysis

    PubMed Central

    Hussain, Joy N; Mantri, Nitin; Cohen, Marc M

    2017-01-01

    Introduction Human sweat is a complex biofluid of interest to diverse scientific fields. Metabolomics analysis of sweat promises to improve screening, diagnosis and self-monitoring of numerous conditions through new applications and greater personalisation of medical interventions. Before these applications can be fully developed, existing methods for the collection, handling, processing and storage of human sweat need to be revised. This review presents a cross-disciplinary overview of the origins, composition, physical characteristics and functional roles of human sweat, and explores the factors involved in standardising sweat collection for metabolomics analysis. Methods A literature review of human sweat analysis over the past 10 years (2006–2016) was performed to identify studies with metabolomics or similarly applicable ‘omics’ analysis. These studies were reviewed with attention to sweat induction and sampling techniques, timing of sweat collection, sweat storage conditions, laboratory derivation, processing and analytical platforms. Results Comparative analysis of 20 studies revealed numerous factors that can significantly impact the validity, reliability and reproducibility of sweat analysis including: anatomical site of sweat sampling, skin integrity and preparation; temperature and humidity at the sweat collection sites; timing and nature of sweat collection; metabolic quenching; transport and storage; qualitative and quantitative measurements of the skin microbiota at sweat collection sites; and individual variables such as diet, emotional state, metabolic conditions, pharmaceutical, recreational drug and supplement use. Conclusion Further development of standard operating protocols for human sweat collection can open the way for sweat metabolomics to significantly add to our understanding of human physiology in health and disease. PMID:28798503

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

    PubMed

    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.

  10. E-Cigarette Affects the Metabolome of Primary Normal Human Bronchial Epithelial Cells

    PubMed Central

    Aug, Argo; Altraja, Siiri; Kilk, Kalle; Porosk, Rando; Soomets, Ursel; Altraja, Alan

    2015-01-01

    E-cigarettes are widely believed to be safer than conventional cigarettes and have been even suggested as aids for smoking cessation. However, while reasonable with some regards, this judgment is not yet supported by adequate biomedical research data. Since bronchial epithelial cells are the immediate target of inhaled toxicants, we hypothesized that exposure to e-cigarettes may affect the metabolome of human bronchial epithelial cells (HBEC) and that the changes are, at least in part, induced by oxidant-driven mechanisms. Therefore, we evaluated the effect of e-cigarette liquid (ECL) on the metabolome of HBEC and examined the potency of antioxidants to protect the cells. We assessed the changes of the intracellular metabolome upon treatment with ECL in comparison of the effect of cigarette smoke condensate (CSC) with mass spectrometry and principal component analysis on air-liquid interface model of normal HBEC. Thereafter, we evaluated the capability of the novel antioxidant tetrapeptide O-methyl-l-tyrosinyl-γ-l-glutamyl-l-cysteinylglycine (UPF1) to attenuate the effect of ECL. ECL caused a significant shift in the metabolome that gradually gained its maximum by the 5th hour and receded by the 7th hour. A second alteration followed at the 13th hour. Treatment with CSC caused a significant initial shift already by the 1st hour. ECL, but not CSC, significantly increased the concentrations of arginine, histidine, and xanthine. ECL, in parallel with CSC, increased the content of adenosine diphosphate and decreased that of three lipid species from the phosphatidylcholine family. UPF1 partially counteracted the ECL-induced deviations, UPF1’s maximum effect occurred at the 5th hour. The data support our hypothesis that ECL profoundly alters the metabolome of HBEC in a manner, which is comparable and partially overlapping with the effect of CSC. Hence, our results do not support the concept of harmlessness of e-cigarettes. PMID:26536230

  11. Targeted High Performance Liquid Chromatography Tandem Mass Spectrometry-based Metabolomics differentiates metabolic syndrome from obesity.

    PubMed

    Zhong, Fanyi; Xu, Mengyang; Bruno, Richard S; Ballard, Kevin D; Zhu, Jiangjiang

    2017-04-01

    Both obesity and the metabolic syndrome are risk factors for type 2 diabetes and cardiovascular disease. Identification of novel biomarkers are needed to distinguish metabolic syndrome from equally obese individuals in order to direct them to early interventions that reduce their risk of developing further health problems. We utilized mass spectrometry-based targeted metabolic profiling of 221 metabolites to evaluate the associations between metabolite profiles and established metabolic syndrome criteria (i.e. elevated waist circumference, hypertension, elevated fasting glucose, elevated triglycerides, and low high-density lipoprotein cholesterol) in plasma samples from obese men ( n = 29; BMI = 35.5 ± 5.2 kg/m 2 ) and women ( n = 40; 34.9 ± 6.7 kg/m 2 ), of which 26 met the criteria for metabolic syndrome (17 men and 9 women). Compared to obese individuals without metabolic syndrome, univariate statistical analysis and partial least squares discriminant analysis showed that a specific group of metabolites from multiple metabolic pathways (i.e. purine metabolism, valine, leucine and isoleucine degradation, and tryptophan metabolism) were associated with the presence of metabolic syndrome. Receiver operating characteristic curves generated based on the PLS-DA models showed excellent areas under the curve (0.85 and 0.96, for metabolites only model and enhanced metabolites model, respectively), high specificities (0.86 and 0.93), and good sensitivities (0.71 and 0.91). Moreover, principal component analysis revealed that metabolic profiles can be used to further differentiate metabolic syndrome with 3 versus 4-5 metabolic syndrome criteria. Collectively, these findings support targeted metabolomics approaches to distinguish metabolic syndrome from obesity alone, and to stratify metabolic syndrome status based on the number of criteria met. Impact statement We utilized mass spectrometry-based targeted metabolic profiling of 221 metabolites to

  12. Metabolomics in Sepsis and Its Impact on Public Health.

    PubMed

    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.

  13. SECIMTools: a suite of metabolomics data analysis tools.

    PubMed

    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.

  14. Vitamins, Metabolomics and Prostate Cancer

    PubMed Central

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

    2016-01-01

    Purpose 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 by which vitamins influence prostate cancer risk. Methods Prostate cancer risk data related to vitamins E, A, and D and metabolomics 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. Results 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 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 metabolomics profiling of fasting serum collected 1-20 years prior to clinical diagnoses found lipid and energy/TCA cycle metabolites, including inositol-1-phosphate, lysolipids, alpha-ketoglutarate, and citrate, significantly associated with risk of aggressive disease. Conclusions 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. PMID:27339624

  15. Vitamins, metabolomics, and prostate cancer.

    PubMed

    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.

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

    PubMed

    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.

  17. Metabolomic Analysis in Heart Failure.

    PubMed

    Ikegami, Ryutaro; Shimizu, Ippei; Yoshida, Yohko; Minamino, Tohru

    2017-12-25

    It is thought that at least 6,500 low-molecular-weight metabolites exist in humans, and these metabolites have various important roles in biological systems in addition to proteins and genes. Comprehensive assessment of endogenous metabolites is called metabolomics, and recent advances in this field have enabled us to understand the critical role of previously unknown metabolites or metabolic pathways in the cardiovascular system. In this review, we will focus on heart failure and how metabolomic analysis has contributed to improving our understanding of the pathogenesis of this critical condition.

  18. Genomic and Metabolomic Profile Associated to Microalbuminuria

    PubMed Central

    Marrachelli, Vannina G.; Monleon, Daniel; Rentero, Pilar; Mansego, María L.; Morales, Jose Manuel; Galan, Inma; Segura, Remedios; Martinez, Fernando; Martin-Escudero, Juan Carlos; Briongos, Laisa; Marin, Pablo; Lliso, Gloria; Chaves, Felipe Javier; Redon, Josep

    2014-01-01

    To identify factors related with the risk to develop microalbuminuria using combined genomic and metabolomic values from a general population study. One thousand five hundred and two subjects, Caucasian, more than 18 years, representative of the general population, were included. Blood pressure measurement and albumin/creatinine ratio were measured in a urine sample. Using SNPlex, 1251 SNPs potentially associated to urinary albumin excretion (UAE) were analyzed. Serum metabolomic profile was assessed by 1H NMR spectra using a Brucker Advance DRX 600 spectrometer. From the total population, 1217 (mean age 54±19, 50.6% men, ACR>30 mg/g in 81 subjects) with high genotyping call rate were analysed. A characteristic metabolomic profile, which included products from mitochondrial and extra mitochondrial metabolism as well as branched amino acids and their derivative signals, were observed in microalbuminuric as compare to normoalbuminuric subjects. The comparison of the metabolomic profile between subjects with different UAE status for each of the genotypes associated to microalbuminuria revealed two SNPs, the rs10492025_TT of RPH3A gene and the rs4359_CC of ACE gene, with minimal or no statistically significant differences. Subjects with and without microalbuminuria, who shared the same genotype and metabolomic profile, differed in age. Microalbuminurics with the CC genotype of the rs4359 polymorphism and with the TT genotype of the rs10492025 polymorphism were seven years older and seventeen years younger, respectively as compared to the whole microalbuminuric subjects. With the same metabolomic environment, characteristic of subjects with microalbuminuria, the TT genotype of the rs10492025 polymorphism seems to increase and the CC genotype of the rs4359 polymorphism seems to reduce risk to develop microalbuminuria. PMID:24918908

  19. Single-cell metabolomics: analytical and biological perspectives.

    PubMed

    Zenobi, R

    2013-12-06

    There is currently much interest in broad molecular profiling of single cells; a cell's metabolome-its full complement of small-molecule metabolites-is a direct indicator of phenotypic diversity of single cells and a nearly immediate readout of how cells react to environmental influences. However, the metabolome is very difficult to measure at the single-cell level because of rapid metabolic dynamics, the structural diversity of the molecules, and the inability to amplify or tag small-molecule metabolites. Measurement techniques including mass spectrometry, capillary electrophoresis, and, to a lesser extent, optical spectroscopy and fluorescence detection have led to impressive advances in single-cell metabolomics. Even though none of these methodologies can currently measure the metabolome of a single cell completely, rapidly, and nondestructively, progress has been sufficient such that the field is witnessing a shift from feasibility studies to investigations that yield new biological insight. Particularly interesting fields of application are cancer biology, stem cell research, and monitoring of xenobiotics and drugs in tissue sections at the single-cell level.

  20. Flux analysis and metabolomics for systematic metabolic engineering of microorganisms.

    PubMed

    Toya, Yoshihiro; Shimizu, Hiroshi

    2013-11-01

    Rational engineering of metabolism is important for bio-production using microorganisms. Metabolic design based on in silico simulations and experimental validation of the metabolic state in the engineered strain helps in accomplishing systematic metabolic engineering. Flux balance analysis (FBA) is a method for the prediction of metabolic phenotype, and many applications have been developed using FBA to design metabolic networks. Elementary mode analysis (EMA) and ensemble modeling techniques are also useful tools for in silico strain design. The metabolome and flux distribution of the metabolic pathways enable us to evaluate the metabolic state and provide useful clues to improve target productivity. Here, we reviewed several computational applications for metabolic engineering by using genome-scale metabolic models of microorganisms. We also discussed the recent progress made in the field of metabolomics and (13)C-metabolic flux analysis techniques, and reviewed these applications pertaining to bio-production development. Because these in silico or experimental approaches have their respective advantages and disadvantages, the combined usage of these methods is complementary and effective for metabolic engineering. Copyright © 2013 Elsevier Inc. All rights reserved.

  1. Metabolomic Quantitative Trait Loci (mQTL) Mapping Implicates the Ubiquitin Proteasome System in Cardiovascular Disease Pathogenesis.

    PubMed

    Kraus, William E; Muoio, Deborah M; Stevens, Robert; Craig, Damian; Bain, James R; Grass, Elizabeth; Haynes, Carol; Kwee, Lydia; Qin, Xuejun; Slentz, Dorothy H; Krupp, Deidre; Muehlbauer, Michael; Hauser, Elizabeth R; Gregory, Simon G; Newgard, Christopher B; Shah, Svati H

    2015-11-01

    Levels of certain circulating short-chain dicarboxylacylcarnitine (SCDA), long-chain dicarboxylacylcarnitine (LCDA) and medium chain acylcarnitine (MCA) metabolites are heritable and predict cardiovascular disease (CVD) events. Little is known about the biological pathways that influence levels of most of these metabolites. Here, we analyzed genetics, epigenetics, and transcriptomics with metabolomics in samples from a large CVD cohort to identify novel genetic markers for CVD and to better understand the role of metabolites in CVD pathogenesis. Using genomewide association in the CATHGEN cohort (N = 1490), we observed associations of several metabolites with genetic loci. Our strongest findings were for SCDA metabolite levels with variants in genes that regulate components of endoplasmic reticulum (ER) stress (USP3, HERC1, STIM1, SEL1L, FBXO25, SUGT1) These findings were validated in a second cohort of CATHGEN subjects (N = 2022, combined p = 8.4x10-6-2.3x10-10). Importantly, variants in these genes independently predicted CVD events. Association of genomewide methylation profiles with SCDA metabolites identified two ER stress genes as differentially methylated (BRSK2 and HOOK2). Expression quantitative trait loci (eQTL) pathway analyses driven by gene variants and SCDA metabolites corroborated perturbations in ER stress and highlighted the ubiquitin proteasome system (UPS) arm. Moreover, culture of human kidney cells in the presence of levels of fatty acids found in individuals with cardiometabolic disease, induced accumulation of SCDA metabolites in parallel with increases in the ER stress marker BiP. Thus, our integrative strategy implicates the UPS arm of the ER stress pathway in CVD pathogenesis, and identifies novel genetic loci associated with CVD event risk.

  2. Metabolomic Quantitative Trait Loci (mQTL) Mapping Implicates the Ubiquitin Proteasome System in Cardiovascular Disease Pathogenesis

    PubMed Central

    Kraus, William E.; Muoio, Deborah M.; Stevens, Robert; Craig, Damian; Bain, James R.; Grass, Elizabeth; Haynes, Carol; Kwee, Lydia; Qin, Xuejun; Slentz, Dorothy H.; Krupp, Deidre; Muehlbauer, Michael; Hauser, Elizabeth R.; Gregory, Simon G.; Newgard, Christopher B.; Shah, Svati H.

    2015-01-01

    Levels of certain circulating short-chain dicarboxylacylcarnitine (SCDA), long-chain dicarboxylacylcarnitine (LCDA) and medium chain acylcarnitine (MCA) metabolites are heritable and predict cardiovascular disease (CVD) events. Little is known about the biological pathways that influence levels of most of these metabolites. Here, we analyzed genetics, epigenetics, and transcriptomics with metabolomics in samples from a large CVD cohort to identify novel genetic markers for CVD and to better understand the role of metabolites in CVD pathogenesis. Using genomewide association in the CATHGEN cohort (N = 1490), we observed associations of several metabolites with genetic loci. Our strongest findings were for SCDA metabolite levels with variants in genes that regulate components of endoplasmic reticulum (ER) stress (USP3, HERC1, STIM1, SEL1L, FBXO25, SUGT1) These findings were validated in a second cohort of CATHGEN subjects (N = 2022, combined p = 8.4x10-6–2.3x10-10). Importantly, variants in these genes independently predicted CVD events. Association of genomewide methylation profiles with SCDA metabolites identified two ER stress genes as differentially methylated (BRSK2 and HOOK2). Expression quantitative trait loci (eQTL) pathway analyses driven by gene variants and SCDA metabolites corroborated perturbations in ER stress and highlighted the ubiquitin proteasome system (UPS) arm. Moreover, culture of human kidney cells in the presence of levels of fatty acids found in individuals with cardiometabolic disease, induced accumulation of SCDA metabolites in parallel with increases in the ER stress marker BiP. Thus, our integrative strategy implicates the UPS arm of the ER stress pathway in CVD pathogenesis, and identifies novel genetic loci associated with CVD event risk. PMID:26540294

  3. Effect of High-Carbohydrate Diet on Plasma Metabolome in Mice with Mitochondrial Respiratory Chain Complex III Deficiency

    PubMed Central

    Rajendran, Jayasimman; Tomašić, Nikica; Kotarsky, Heike; Hansson, Eva; Velagapudi, Vidya; Kallijärvi, Jukka; Fellman, Vineta

    2016-01-01

    Mitochondrial disorders cause energy failure and metabolic derangements. Metabolome profiling in patients and animal models may identify affected metabolic pathways and reveal new biomarkers of disease progression. Using liver metabolomics we have shown a starvation-like condition in a knock-in (Bcs1lc.232A>G) mouse model of GRACILE syndrome, a neonatal lethal respiratory chain complex III dysfunction with hepatopathy. Here, we hypothesized that a high-carbohydrate diet (HCD, 60% dextrose) will alleviate the hypoglycemia and promote survival of the sick mice. However, when fed HCD the homozygotes had shorter survival (mean ± SD, 29 ± 2.5 days, n = 21) than those on standard diet (33 ± 3.8 days, n = 30), and no improvement in hypoglycemia or liver glycogen depletion. We investigated the plasma metabolome of the HCD- and control diet-fed mice and found that several amino acids and urea cycle intermediates were increased, and arginine, carnitines, succinate, and purine catabolites decreased in the homozygotes. Despite reduced survival the increase in aromatic amino acids, an indicator of liver mitochondrial dysfunction, was normalized on HCD. Quantitative enrichment analysis revealed that glycine, serine and threonine metabolism, phenylalanine and tyrosine metabolism, and urea cycle were also partly normalized on HCD. This dietary intervention revealed an unexpected adverse effect of high-glucose diet in complex III deficiency, and suggests that plasma metabolomics is a valuable tool in evaluation of therapies in mitochondrial disorders. PMID:27809283

  4. Targeted Metabolomic Pathway Analysis and Validation Revealed Glutamatergic Disorder in the Prefrontal Cortex among the Chronic Social Defeat Stress Mice Model of Depression.

    PubMed

    Wang, Wei; Guo, Hua; Zhang, Shu-Xiao; Li, Juan; Cheng, Ke; Bai, Shun-Jie; Yang, De-Yu; Wang, Hai-Yang; Liang, Zi-Hong; Liao, Li; Sun, Lin; Xie, Peng

    2016-10-07

    Major depressive disorder (MDD) is a severe psychiatric disease that has critically affected life quality for millions of people. Chronic stress is gradually recognized as a primary pathogenesis risk factor of MDD. Despite the remarkable progress in mechanism research, the pathogenesis mechanism of MDD is still not well understood. Therefore, we conducted a liquid chromatography-tandem mass spectrometry (LC-MS/MS) detection of 25 major metabolites of tryptophanic, GABAergic, and catecholaminergic pathways in the prefontal cortex (PFC) of mice in chronic social defeat stress (CSDS). The depressed mice exhibit significant reduction of glutamate in the GABAergic pathway and an increase of L-DOPA and vanillylmandelic acid in catecholaminergic pathways. The data of real-time-quantitative polymerase chain reaction (RT-qPCR) and Western blotting analysis revealed an altered level of glutamatergic circuitry. The metabolomic and molecular data reveal that the glutamatergic disorder in mice shed lights to reveal a mechanism on depression-like and stress resilient phenotype.

  5. Mathematical Modeling and Dynamic Simulation of Metabolic Reaction Systems Using Metabolome Time Series Data.

    PubMed

    Sriyudthsak, Kansuporn; Shiraishi, Fumihide; Hirai, Masami Yokota

    2016-01-01

    The high-throughput acquisition of metabolome data is greatly anticipated for the complete understanding of cellular metabolism in living organisms. A variety of analytical technologies have been developed to acquire large-scale metabolic profiles under different biological or environmental conditions. Time series data are useful for predicting the most likely metabolic pathways because they provide important information regarding the accumulation of metabolites, which implies causal relationships in the metabolic reaction network. Considerable effort has been undertaken to utilize these data for constructing a mathematical model merging system properties and quantitatively characterizing a whole metabolic system in toto. However, there are technical difficulties between benchmarking the provision and utilization of data. Although, hundreds of metabolites can be measured, which provide information on the metabolic reaction system, simultaneous measurement of thousands of metabolites is still challenging. In addition, it is nontrivial to logically predict the dynamic behaviors of unmeasurable metabolite concentrations without sufficient information on the metabolic reaction network. Yet, consolidating the advantages of advancements in both metabolomics and mathematical modeling remain to be accomplished. This review outlines the conceptual basis of and recent advances in technologies in both the research fields. It also highlights the potential for constructing a large-scale mathematical model by estimating model parameters from time series metabolome data in order to comprehensively understand metabolism at the systems level.

  6. Fish mucus metabolome reveals fish life-history traits

    NASA Astrophysics Data System (ADS)

    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.

  7. High-resolution metabolomics of occupational exposure to trichloroethylene

    PubMed Central

    Walker, Douglas I; Uppal, Karan; Zhang, Luoping; Vermeulen, Roel; Smith, Martyn; Hu, Wei; Purdue, Mark P; Tang, Xiaojiang; Reiss, Boris; Kim, Sungkyoon; Li, Laiyu; Huang, Hanlin; Pennell, Kurt D; Jones, Dean P; Rothman, Nathaniel; Lan, Qing

    2016-01-01

    Background: Occupational exposure to trichloroethylene (TCE) has been linked to adverse health outcomes including non-Hodgkin’s lymphoma and kidney and liver cancer; however, TCE’s mode of action for development of these diseases in humans is not well understood. Methods: Non-targeted metabolomics analysis of plasma obtained from 80 TCE-exposed workers [full shift exposure range of 0.4 to 230 parts-per-million of air (ppma)] and 95 matched controls were completed by ultra-high resolution mass spectrometry. Biological response to TCE exposure was determined using a metabolome-wide association study (MWAS) framework, with metabolic changes and plasma TCE metabolites evaluated by dose-response and pathway enrichment. Biological perturbations were then linked to immunological, renal and exposure molecular markers measured in the same population. Results: Metabolic features associated with TCE exposure included known TCE metabolites, unidentifiable chlorinated compounds and endogenous metabolites. Exposure resulted in a systemic response in endogenous metabolism, including disruption in purine catabolism and decreases in sulphur amino acid and bile acid biosynthesis pathways. Metabolite associations with TCE exposure included uric acid (β = 0.13, P-value = 3.6 × 10−5), glutamine (β = 0.08, P-value = 0.0013), cystine (β = 0.75, P-value = 0.0022), methylthioadenosine (β = −1.6, P-value = 0.0043), taurine (β = −2.4, P-value = 0.0011) and chenodeoxycholic acid (β = −1.3, P-value = 0.0039), which are consistent with known toxic effects of TCE, including immunosuppression, hepatotoxicity and nephrotoxicity. Correlation with additional exposure markers and physiological endpoints supported known disease associations. Conclusions: High-resolution metabolomics correlates measured occupational exposure to internal dose and metabolic response, providing insight into molecular mechanisms of exposure

  8. Effects of MeJA on Arabidopsis metabolome under endogenous JA deficiency

    NASA Astrophysics Data System (ADS)

    Cao, Jingjing; Li, Mengya; Chen, Jian; Liu, Pei; Li, Zhen

    2016-11-01

    Jasmonates (JAs) play important roles in plant growth, development and defense. Comprehensive metabolomics profiling of plants under JA treatment provides insights into the interaction and regulation network of plant hormones. Here we applied high resolution mass spectrometry based metabolomics approach on Arabidopsis wild type and JA synthesis deficiency mutant opr3. The effects of exogenous MeJA treatment on the metabolites of opr3 were investigated. More than 10000 ion signals were detected and more than 2000 signals showed significant variation in different genotypes and treatment groups. Multivariate statistic analyses (PCA and PLS-DA) were performed and a differential compound library containing 174 metabolites with high resolution precursor ion-product ions pairs was obtained. Classification and pathway analysis of 109 identified compounds in this library showed that glucosinolates and tryptophan metabolism, amino acids and small peptides metabolism, lipid metabolism, especially fatty acyls metabolism, were impacted by endogenous JA deficiency and exogenous MeJA treatment. These results were further verified by quantitative reverse transcription PCR (RT-qPCR) analysis of 21 related genes involved in the metabolism of glucosinolates, tryptophan and α-linolenic acid pathways. The results would greatly enhance our understanding of the biological functions of JA.

  9. 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.

    PubMed

    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.

  10. LC-MS Data Processing with MAVEN: A Metabolomic Analysis and Visualization Engine

    PubMed Central

    Clasquin, Michelle F.; Melamud, Eugene; Rabinowitz, Joshua D.

    2014-01-01

    MAVEN is an open-source software program for interactive processing of LC-MS-based metabolomics data. MAVEN enables rapid and reliable metabolite quantitation from multiple reaction monitoring data or high-resolution full-scan mass spectrometry data. It automatically detects and reports peak intensities for isotope-labeled metabolites. Menu-driven, click-based navigation allows visualization of raw and analyzed data. Here we provide a User Guide for MAVEN. Step-by-step instructions are provided for data import, peak alignment across samples, identification of metabolites that differ strongly between biological conditions, quantitation and visualization of isotope-labeling patterns, and export of tables of metabolite-specific peak intensities. Together, these instructions describe a workflow that allows efficient processing of raw LC-MS data into a form ready for biological analysis. PMID:22389014

  11. UPLC-MS for metabolomics: a giant step forward in support of pharmaceutical research.

    PubMed

    Nassar, Ala F; Wu, Terence; Nassar, Samuel F; Wisnewski, Adam V

    2017-02-01

    Metabolomics is a relatively new and rapidly growing area of post-genomic biological research. As use of metabolomics technology grows throughout the spectrum of drug discovery and development, and its applications broaden, its impact is expanding dramatically. This review seeks to provide the reader with a brief history of the development of metabolomics, its significance and strategies for conducting metabolomics studies. The most widely used analytical tools for metabolomics: NMR, LC-MS and GC-MS, are discussed along with considerations for their use. Herein, we will show how metabolomics can assist in pharmaceutical research studies, such as pharmacology and toxicology, and discuss some examples of the importance of metabolomics analysis in research and development. Copyright © 2016 Elsevier Ltd. All rights reserved.

  12. Targeted quantitative analysis of Streptococcus pyogenes virulence factors by multiple reaction monitoring.

    PubMed

    Lange, Vinzenz; Malmström, Johan A; Didion, John; King, Nichole L; Johansson, Björn P; Schäfer, Juliane; Rameseder, Jonathan; Wong, Chee-Hong; Deutsch, Eric W; Brusniak, Mi-Youn; Bühlmann, Peter; Björck, Lars; Domon, Bruno; Aebersold, Ruedi

    2008-08-01

    In many studies, particularly in the field of systems biology, it is essential that identical protein sets are precisely quantified in multiple samples such as those representing differentially perturbed cell states. The high degree of reproducibility required for such experiments has not been achieved by classical mass spectrometry-based proteomics methods. In this study we describe the implementation of a targeted quantitative approach by which predetermined protein sets are first identified and subsequently quantified at high sensitivity reliably in multiple samples. This approach consists of three steps. First, the proteome is extensively mapped out by multidimensional fractionation and tandem mass spectrometry, and the data generated are assembled in the PeptideAtlas database. Second, based on this proteome map, peptides uniquely identifying the proteins of interest, proteotypic peptides, are selected, and multiple reaction monitoring (MRM) transitions are established and validated by MS2 spectrum acquisition. This process of peptide selection, transition selection, and validation is supported by a suite of software tools, TIQAM (Targeted Identification for Quantitative Analysis by MRM), described in this study. Third, the selected target protein set is quantified in multiple samples by MRM. Applying this approach we were able to reliably quantify low abundance virulence factors from cultures of the human pathogen Streptococcus pyogenes exposed to increasing amounts of plasma. The resulting quantitative protein patterns enabled us to clearly define the subset of virulence proteins that is regulated upon plasma exposure.

  13. Navigating freely-available software tools for metabolomics analysis.

    PubMed

    Spicer, Rachel; Salek, Reza M; Moreno, Pablo; Cañueto, Daniel; Steinbeck, Christoph

    2017-01-01

    The field of metabolomics has expanded greatly over the past two decades, both as an experimental science with applications in many areas, as well as in regards to data standards and bioinformatics software tools. The diversity of experimental designs and instrumental technologies used for metabolomics has led to the need for distinct data analysis methods and the development of many software tools. To compile a comprehensive list of the most widely used freely available software and tools that are used primarily in metabolomics. The most widely used tools were selected for inclusion in the review by either ≥ 50 citations on Web of Science (as of 08/09/16) or the use of the tool being reported in the recent Metabolomics Society survey. Tools were then categorised by the type of instrumental data (i.e. LC-MS, GC-MS or NMR) and the functionality (i.e. pre- and post-processing, statistical analysis, workflow and other functions) they are designed for. A comprehensive list of the most used tools was compiled. Each tool is discussed within the context of its application domain and in relation to comparable tools of the same domain. An extended list including additional tools is available at https://github.com/RASpicer/MetabolomicsTools which is classified and searchable via a simple controlled vocabulary. This review presents the most widely used tools for metabolomics analysis, categorised based on their main functionality. As future work, we suggest a direct comparison of tools' abilities to perform specific data analysis tasks e.g. peak picking.

  14. Metabolomic Assessment of Embryo Viability

    PubMed Central

    Uyar, Asli; Seli, Emre

    2014-01-01

    Preimplantation embryo metabolism demonstrates distinctive characteristics associated with the developmental potential of embryos. On this basis, metabolite content of culture media was hypothesized to reflect the implantation potential of individual embryos. This hypothesis was tested in consecutive studies reporting a significant association between culture media metabolites and embryo development or clinical pregnancy. The need for a noninvasive, reliable, and rapid embryo assessment strategy promoted metabolomics studies in vitro fertilization (IVF) in an effort to increase success rates of single embryo transfers. With the advance of analytical techniques and bioinformatics, commercial instruments were developed to predict embryo viability using spectroscopic analysis of surplus culture media. However, despite the initial promising results from proof-of-principal studies, recent randomized controlled trials using commercial instruments failed to show a consistent benefit in improving pregnancy rates when metabolomics is used as an adjunct to morphology. At present, the application of metabolomics technology in clinical IVF laboratory requires the elimination of factors underlying inconsistent findings, when possible, and development of reliable predictive models accounting for all possible sources of bias throughout the embryo selection process. PMID:24515909

  15. Qualitative metabolomics profiling of serum and bile from dogs with gallbladder mucocele formation.

    PubMed

    Gookin, Jody L; Mathews, Kyle G; Cullen, John; Seiler, Gabriela

    2018-01-01

    Mucocele formation is characterized by secretion of abnormally thick mucus by the gallbladder epithelium of dogs that may cause obstruction of the bile duct or rupture of the gallbladder. The disease is increasingly recognized and is associated with a high morbidity and mortality. The cause of gallbladder mucocele formation in dogs is unknown. There is a strong breed predisposition and affected dogs have a high incidence of concurrent endocrinopathy or hyperlipidemia. These observations suggest a significant influence of both genetic and metabolic factors on disease pathogenesis. In this study, we investigated a theory that mucocele formation is associated with a syndrome of metabolic disruption. We surmised that a global, untargeted metabolomics approach could provide unique insight into the systemic pathogenesis of gallbladder mucocele formation and identify specific compounds as candidate biomarkers or treatment targets. Moreover, concurrent examination of the serum and hepatic duct bile metabolome would enable the construction of mechanism-based theories or identification of specific compounds responsible for altered function of the gallbladder epithelium. Abnormalities observed in dogs with gallbladder mucocele formation, including a 33-fold decrease in serum adenosine 5'-monophosphate (AMP), lower quantities of precursors required for synthesis of energy transporting nucleotides, and increases in citric acid cycle intermediates, suggest excess metabolic energy and a carbon surplus. Altered quantities of compounds involved in protein translation and RNA turnover, together with accumulation of gamma-glutamylated and N-acetylated amino acids in serum suggest abnormal regulation of protein and amino acid metabolism. Increases in lathosterol and 7α-hydroxycholesterol suggest a primary increase in cholesterol synthesis and diversion to bile acid formation. A number of specific biomarker compounds were identified for their ability to distinguish between control

  16. Target-responsive DNAzyme cross-linked hydrogel for visual quantitative detection of lead.

    PubMed

    Huang, Yishun; Ma, Yanli; Chen, Yahong; Wu, Xuemeng; Fang, Luting; Zhu, Zhi; Yang, Chaoyong James

    2014-11-18

    Because of the severe health risks associated with lead pollution, rapid, sensitive, and portable detection of low levels of Pb(2+) in biological and environmental samples is of great importance. In this work, a Pb(2+)-responsive hydrogel was prepared using a DNAzyme and its substrate as cross-linker for rapid, sensitive, portable, and quantitative detection of Pb(2+). Gold nanoparticles (AuNPs) were first encapsulated in the hydrogel as an indicator for colorimetric analysis. In the absence of lead, the DNAzyme is inactive, and the substrate cross-linker maintains the hydrogel in the gel form. In contrast, the presence of lead activates the DNAzyme to cleave the substrate, decreasing the cross-linking density of the hydrogel and resulting in dissolution of the hydrogel and release of AuNPs for visual detection. As low as 10 nM Pb(2+) can be detected by the naked eye. Furthermore, to realize quantitative visual detection, a volumetric bar-chart chip (V-chip) was used for quantitative readout of the hydrogel system by replacing AuNPs with gold-platinum core-shell nanoparticles (Au@PtNPs). The Au@PtNPs released from the hydrogel upon target activation can efficiently catalyze the decomposition of H2O2 to generate a large volume of O2. The gas pressure moves an ink bar in the V-chip for portable visual quantitative detection of lead with a detection limit less than 5 nM. The device was able to detect lead in digested blood with excellent accuracy. The method developed can be used for portable lead quantitation in many applications. Furthermore, the method can be further extended to portable visual quantitative detection of a variety of targets by replacing the lead-responsive DNAzyme with other DNAzymes.

  17. Quantitative comparison of tumor delivery for multiple targeted nanoparticles simultaneously by multiplex ICP-MS.

    PubMed

    Elias, Andrew; Crayton, Samuel H; Warden-Rothman, Robert; Tsourkas, Andrew

    2014-07-28

    Given the rapidly expanding library of disease biomarkers and targeting agents, the number of unique targeted nanoparticles is growing exponentially. The high variability and expense of animal testing often makes it unfeasible to examine this large number of nanoparticles in vivo. This often leads to the investigation of a single formulation that performed best in vitro. However, nanoparticle performance in vivo depends on many variables, many of which cannot be adequately assessed with cell-based assays. To address this issue, we developed a lanthanide-doped nanoparticle method that allows quantitative comparison of multiple targeted nanoparticles simultaneously. Specifically, superparamagnetic iron oxide (SPIO) nanoparticles with different targeting ligands were created, each with a unique lanthanide dopant. Following the simultaneous injection of the various SPIO compositions into tumor-bearing mice, inductively coupled plasma mass spectroscopy was used to quantitatively and orthogonally assess the concentration of each SPIO composition in serial blood and resected tumor samples.

  18. Quantitative Comparison of Tumor Delivery for Multiple Targeted Nanoparticles Simultaneously by Multiplex ICP-MS

    PubMed Central

    Elias, Andrew; Crayton, Samuel H.; Warden-Rothman, Robert; Tsourkas, Andrew

    2014-01-01

    Given the rapidly expanding library of disease biomarkers and targeting agents, the number of unique targeted nanoparticles is growing exponentially. The high variability and expense of animal testing often makes it unfeasible to examine this large number of nanoparticles in vivo. This often leads to the investigation of a single formulation that performed best in vitro. However, nanoparticle performance in vivo depends on many variables, many of which cannot be adequately assessed with cell-based assays. To address this issue, we developed a lanthanide-doped nanoparticle method that allows quantitative comparison of multiple targeted nanoparticles simultaneously. Specifically, superparamagnetic iron oxide (SPIO) nanoparticles with different targeting ligands were created, each with a unique lanthanide dopant. Following the simultaneous injection of the various SPIO compositions into tumor-bearing mice, inductively coupled plasma mass spectroscopy was used to quantitatively and orthogonally assess the concentration of each SPIO composition in serial blood and resected tumor samples. PMID:25068300

  19. [Development of Plant Metabolomics and Medicinal Plant Genomics].

    PubMed

    Saito, Kazuki

    2018-01-01

     A variety of chemicals produced by plants, often referred to as 'phytochemicals', have been used as medicines, food, fuels and industrial raw materials. Recent advances in the study of genomics and metabolomics in plant science have accelerated our understanding of the mechanisms, regulation and evolution of the biosynthesis of specialized plant products. We can now address such questions as how the metabolomic diversity of plants is originated at the levels of genome, and how we should apply this knowledge to drug discovery, industry and agriculture. Our research group has focused on metabolomics-based functional genomics over the last 15 years and we have developed a new research area called 'Phytochemical Genomics'. In this review, the development of a research platform for plant metabolomics is discussed first, to provide a better understanding of the chemical diversity of plants. Then, representative applications of metabolomics to functional genomics in a model plant, Arabidopsis thaliana, are described. The extension of integrated multi-omics analyses to non-model specialized plants, e.g., medicinal plants, is presented, including the identification of novel genes, metabolites and networks for the biosynthesis of flavonoids, alkaloids, sulfur-containing metabolites and terpenoids. Further, functional genomics studies on a variety of medicinal plants is presented. I also discuss future trends in pharmacognosy and related sciences.

  20. Advances in computational metabolomics and databases deepen the understanding of metabolisms.

    PubMed

    Tsugawa, Hiroshi

    2018-01-29

    Mass spectrometry (MS)-based metabolomics is the popular platform for metabolome analyses. Computational techniques for the processing of MS raw data, for example, feature detection, peak alignment, and the exclusion of false-positive peaks, have been established. The next stage of untargeted metabolomics would be to decipher the mass fragmentation of small molecules for the global identification of human-, animal-, plant-, and microbiota metabolomes, resulting in a deeper understanding of metabolisms. This review is an update on the latest computational metabolomics including known/expected structure databases, chemical ontology classifications, and mass spectrometry cheminformatics for the interpretation of mass fragmentations and for the elucidation of unknown metabolites. The importance of metabolome 'databases' and 'repositories' is also discussed because novel biological discoveries are often attributable to the accumulation of data, to relational databases, and to their statistics. Lastly, a practical guide for metabolite annotations is presented as the summary of this review. Copyright © 2018 Elsevier Ltd. All rights reserved.

  1. Current Challenges in Plant Eco-Metabolomics

    PubMed Central

    Peters, Kristian; Worrich, Anja; Alka, Oliver; Balcke, Gerd; Bruelheide, Helge; Dietz, Sophie; Dührkop, Kai; Heinig, Uwe; Kücklich, Marlen; Müller, Caroline; Poeschl, Yvonne; Pohnert, Georg; Ruttkies, Christoph; Schweiger, Rabea; Shahaf, Nir; Tortosa, Maria; Ueberschaar, Nico; Velasco, Pablo; Weiß, Brigitte M.; van Dam, Nicole M.

    2018-01-01

    The relatively new research discipline of Eco-Metabolomics is the application of metabolomics techniques to ecology with the aim to characterise biochemical interactions of organisms across different spatial and temporal scales. Metabolomics is an untargeted biochemical approach to measure many thousands of metabolites in different species, including plants and animals. Changes in metabolite concentrations can provide mechanistic evidence for biochemical processes that are relevant at ecological scales. These include physiological, phenotypic and morphological responses of plants and communities to environmental changes and also interactions with other organisms. Traditionally, research in biochemistry and ecology comes from two different directions and is performed at distinct spatiotemporal scales. Biochemical studies most often focus on intrinsic processes in individuals at physiological and cellular scales. Generally, they take a bottom-up approach scaling up cellular processes from spatiotemporally fine to coarser scales. Ecological studies usually focus on extrinsic processes acting upon organisms at population and community scales and typically study top-down and bottom-up processes in combination. Eco-Metabolomics is a transdisciplinary research discipline that links biochemistry and ecology and connects the distinct spatiotemporal scales. In this review, we focus on approaches to study chemical and biochemical interactions of plants at various ecological levels, mainly plant–organismal interactions, and discuss related examples from other domains. We present recent developments and highlight advancements in Eco-Metabolomics over the last decade from various angles. We further address the five key challenges: (1) complex experimental designs and large variation of metabolite profiles; (2) feature extraction; (3) metabolite identification; (4) statistical analyses; and (5) bioinformatics software tools and workflows. The presented solutions to these

  2. Counting missing values in a metabolite-intensity data set for measuring the analytical performance of a metabolomics platform.

    PubMed

    Huan, Tao; Li, Liang

    2015-01-20

    Metabolomics requires quantitative comparison of individual metabolites present in an entire sample set. Unfortunately, missing intensity values in one or more samples are very common. Because missing values can have a profound influence on metabolomic results, the extent of missing values found in a metabolomic data set should be treated as an important parameter for measuring the analytical performance of a technique. In this work, we report a study on the scope of missing values and a robust method of filling the missing values in a chemical isotope labeling (CIL) LC-MS metabolomics platform. Unlike conventional LC-MS, CIL LC-MS quantifies the concentration differences of individual metabolites in two comparative samples based on the mass spectral peak intensity ratio of a peak pair from a mixture of differentially labeled samples. We show that this peak-pair feature can be explored as a unique means of extracting metabolite intensity information from raw mass spectra. In our approach, a peak-pair peaking algorithm, IsoMS, is initially used to process the LC-MS data set to generate a CSV file or table that contains metabolite ID and peak ratio information (i.e., metabolite-intensity table). A zero-fill program, freely available from MyCompoundID.org , is developed to automatically find a missing value in the CSV file and go back to the raw LC-MS data to find the peak pair and, then, calculate the intensity ratio and enter the ratio value into the table. Most of the missing values are found to be low abundance peak pairs. We demonstrate the performance of this method in analyzing an experimental and technical replicate data set of human urine metabolome. Furthermore, we propose a standardized approach of counting missing values in a replicate data set as a way of gauging the extent of missing values in a metabolomics platform. Finally, we illustrate that applying the zero-fill program, in conjunction with dansylation CIL LC-MS, can lead to a marked improvement in

  3. Impact of Intestinal Microbiota on Intestinal Luminal Metabolome

    PubMed Central

    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 < 0.05), 77 metabolites were present in significantly lower concentrations and/or incidence in the GF mice than in the Ex-GF mice (p < 0.05), and 56 metabolites showed no differences in the concentration or incidence between GF and Ex-GF mice. These indicate that intestinal microbiota highly influenced the colonic luminal metabolome and a comprehensive understanding of intestinal luminal metabolome is critical for clarifying host-intestinal bacterial interactions. PMID:22724057

  4. Clinical Metabolomics in Neonatology: From Metabolites to Diseases.

    PubMed

    Fanos, Vassilios; Pintus, Roberta; Dessì, Angelica

    2018-01-01

    Today, disorders that affect the newborn remain a challenge for physicians because of the enigmatic pathophysiology and difficulties in treating such delicate patients. Metabolomics, the "omics" science that studies the metabolome, namely the metabolites present in biological fluids, such as saliva, blood, sweat, and breast milk in a given time or condition, can be useful in helping neonatologists to prevent, diagnose, and treat diseases affecting the neonate, especially those with higher mortality rates. Since it is a relatively new technology, studies of its application in neonatology are limited. The aims of this review are to present metabolomics data on relevant neonatal disorders and to identify and discuss the most important 5 metabolites and their clinical significance rather than focusing on each disorder. The preliminary data are promising but further studies on metab-olomics in neonatology are needed together with the standardization of results before their application in clinical practice. © 2018 S. Karger AG, Basel.

  5. Untargeted metabolomics studies employing NMR and LC–MS reveal metabolic coupling between Nanoarcheum equitans and its archaeal host Ignicoccus hospitalis

    DOE PAGES

    Hamerly, Timothy; Tripet, Brian P.; Tigges, Michelle; ...

    2014-11-05

    Interactions between species are the basis of microbial community formation and infectious diseases. Systems biology enables the construction of complex models describing such interactions, leading to a better understanding of disease states and communities. However, before interactions between complex organisms can be understood, metabolic and energetic implications of simpler real-world host-microbe systems must be worked out. To this effect, untargeted metabolomics experiments were conducted and integrated with proteomics data to characterize key molecular-level interactions between two hyperthermophilic microbial species, both of which have reduced genomes. Metabolic changes and transfer of metabolites between the archaea Ignicoccus hospitalis and Nanoarcheum equitans weremore » investigated using integrated LC–MS and NMR metabolomics. The study of such a system is challenging, as no genetic tools are available, growth in the laboratory is challenging, and mechanisms by which they interact are unknown. Together with information about relative enzyme levels obtained from shotgun proteomics, the metabolomics data provided useful insights into metabolic pathways and cellular networks of I. hospitalis that are impacted by the presence of N. equitans, including arginine, isoleucine, and CTP biosynthesis. On the organismal level, the data indicate that N. equitans exploits metabolites generated by I. hospitalis to satisfy its own metabolic needs. Lastly, this finding is based on N. equitans’s consumption of a significant fraction of the metabolite pool in I. hospitalis that cannot solely be attributed to increased biomass production for N. equitans. Combining LC–MS and NMR metabolomics datasets improved coverage of the metabolome and enhanced the identification and quantitation of cellular metabolites.« less

  6. Untargeted metabolomics studies employing NMR and LC-MS reveal metabolic coupling between Nanoarcheum equitans and its archaeal host Ignicoccus hospitalis.

    PubMed

    Hamerly, Timothy; Tripet, Brian P; Tigges, Michelle; Giannone, Richard J; Wurch, Louie; Hettich, Robert L; Podar, Mircea; Copié, Valerie; Bothner, Brian

    2015-08-01

    Interspecies interactions are the basis of microbial community formation and infectious diseases. Systems biology enables the construction of complex models describing such interactions, leading to a better understanding of disease states and communities. However, before interactions between complex organisms can be understood, metabolic and energetic implications of simpler real-world host-microbe systems must be worked out. To this effect, untargeted metabolomics experiments were conducted and integrated with proteomics data to characterize key molecular-level interactions between two hyperthermophilic microbial species, both of which have reduced genomes. Metabolic changes and transfer of metabolites between the archaea Ignicoccus hospitalis and Nanoarcheum equitans were investigated using integrated LC-MS and NMR metabolomics. The study of such a system is challenging, as no genetic tools are available, growth in the laboratory is challenging, and mechanisms by which they interact are unknown. Together with information about relative enzyme levels obtained from shotgun proteomics, the metabolomics data provided useful insights into metabolic pathways and cellular networks of I. hospitalis that are impacted by the presence of N. equitans , including arginine, isoleucine, and CTP biosynthesis. On the organismal level, the data indicate that N. equitans exploits metabolites generated by I. hospitalis to satisfy its own metabolic needs. This finding is based on N. equitans 's consumption of a significant fraction of the metabolite pool in I. hospitalis that cannot solely be attributed to increased biomass production for N. equitans . Combining LC-MS and NMR metabolomics datasets improved coverage of the metabolome and enhanced the identification and quantitation of cellular metabolites.

  7. Untargeted metabolomics studies employing NMR and LC-MS reveal metabolic coupling between Nanoarcheum equitans and its archaeal host Ignicoccus hospitalis

    PubMed Central

    Hamerly, Timothy; Tripet, Brian P.; Tigges, Michelle; Giannone, Richard J.; Wurch, Louie; Hettich, Robert L.; Podar, Mircea; Copié, Valerie; Bothner, Brian

    2014-01-01

    Interspecies interactions are the basis of microbial community formation and infectious diseases. Systems biology enables the construction of complex models describing such interactions, leading to a better understanding of disease states and communities. However, before interactions between complex organisms can be understood, metabolic and energetic implications of simpler real-world host-microbe systems must be worked out. To this effect, untargeted metabolomics experiments were conducted and integrated with proteomics data to characterize key molecular-level interactions between two hyperthermophilic microbial species, both of which have reduced genomes. Metabolic changes and transfer of metabolites between the archaea Ignicoccus hospitalis and Nanoarcheum equitans were investigated using integrated LC-MS and NMR metabolomics. The study of such a system is challenging, as no genetic tools are available, growth in the laboratory is challenging, and mechanisms by which they interact are unknown. Together with information about relative enzyme levels obtained from shotgun proteomics, the metabolomics data provided useful insights into metabolic pathways and cellular networks of I. hospitalis that are impacted by the presence of N. equitans, including arginine, isoleucine, and CTP biosynthesis. On the organismal level, the data indicate that N. equitans exploits metabolites generated by I. hospitalis to satisfy its own metabolic needs. This finding is based on N. equitans’s consumption of a significant fraction of the metabolite pool in I. hospitalis that cannot solely be attributed to increased biomass production for N. equitans. Combining LC-MS and NMR metabolomics datasets improved coverage of the metabolome and enhanced the identification and quantitation of cellular metabolites. PMID:26273237

  8. Psychosocial Stress and Ovarian Cancer Risk: Metabolomics and Perceived Stress

    DTIC Science & Technology

    2015-10-01

    AWARD NUMBER: W81XWH-13-1-0493 TITLE: Psychosocial Stress and Ovarian Cancer Risk: Metabolomics and Perceived Stress PRINCIPAL INVESTIGATOR...SUBTITLE 5a. CONTRACT NUMBER Psychosocial Stress and Ovarian Cancer Risk: Metabolomics and Perceived Stress 5b. GRANT NUMBER W81XWH-13-1-0493 5c...TERMS ovarian cancer, psychosocial stress, depression, anxiety, social support, metabolomics 16. SECURITY CLASSIFICATION OF: 17. LIMITATION OF

  9. Glucose enhances tilapia against Edwardsiella tarda infection through metabolome reprogramming.

    PubMed

    Zeng, Zao-hai; Du, Chao-Chao; Liu, Shi-Rao; Li, Hui; Peng, Xuan-Xian; Peng, Bo

    2017-02-01

    We have recently reported that the survival of tilapia, Oreochromis niloticus, during Edwardsiella tarda infection is tightly associated with their metabolome, where the survived O. niloticus has distinct metabolomic profile to dying O. niloticus. Glucose is the key metabolite to distinguish the survival- and dying-metabolome. More importantly, exogenous administration of glucose to the fish greatly enhances their survival for the infection, indicating the functional roles of glucose in metabolome repurposing, known as reprogramming metabolomics. However, the underlying information for the reprogramming is not yet available. Here, GC/MS based metabolomics is used to understand the mechanisms by which how exogenous glucose elevates O. niloticus, anti-infectious ability to E. tarda. Results showed that exogenous glucose promotes stearic acid and palmitic acid biosynthesis but attenuates TCA cycle to potentiate O. niloticus against bacterial infection, which is confirmed by the fact that exogenous stearic acid increases immune protection in O. niloticus against E. tarda infection in a manner of Mx protein. These results indicate that exogenous glucose reprograms O. niloticus anti-infective metabolome that characterizes elevation of stearic acid and palmitic acid and attenuation of the TCA cycle. Therefore, our results proposed a novel mechanism that glucose promotes unsaturated fatty acid biosynthesis to cope with infection, thereby highlighting a potential way of enhancing fish immunity in aquaculture. Copyright © 2016 Elsevier Ltd. All rights reserved.

  10. MetabolitePredict: A de novo human metabolomics prediction system and its applications in rheumatoid arthritis.

    PubMed

    Wang, QuanQiu; Xu, Rong

    2017-07-01

    Human metabolomics has great potential in disease mechanism understanding, early diagnosis, and therapy. Existing metabolomics studies are often based on profiling patient biofluids and tissue samples and are difficult owing to the challenges of sample collection and data processing. Here, we report an alternative approach and developed a computation-based prediction system, MetabolitePredict, for disease metabolomics biomarker prediction. We applied MetabolitePredict to identify metabolite biomarkers and metabolite targeting therapies for rheumatoid arthritis (RA), a last-lasting complex disease with multiple genetic and environmental factors involved. MetabolitePredict is a de novo prediction system. It first constructs a disease-specific genetic profile using genes and pathways data associated with an input disease. It then constructs genetic profiles for a total of 259,170 chemicals/metabolites using known chemical genetics and human metabolomic data. MetabolitePredict prioritizes metabolites for a given disease based on the genetic profile similarities between disease and metabolites. We evaluated MetabolitePredict using 63 known RA-associated metabolites. MetabolitePredict found 24 of the 63 metabolites (recall: 0.38) and ranked them highly (mean ranking: top 4.13%, median ranking: top 1.10%, P-value: 5.08E-19). MetabolitePredict performed better than an existing metabolite prediction system, PROFANCY, in predicting RA-associated metabolites (PROFANCY: recall: 0.31, mean ranking: 20.91%, median ranking: 16.47%, P-value: 3.78E-7). Short-chain fatty acids (SCFAs), the abundant metabolites of gut microbiota in the fermentation of fiber, ranked highly (butyrate, 0.03%; acetate, 0.05%; propionate, 0.38%). Finally, we established MetabolitePredict's potential in novel metabolite targeting for disease treatment: MetabolitePredict ranked highly three known metabolite inhibitors for RA treatments (methotrexate:0.25%; leflunomide: 0.56%; sulfasalazine: 0

  11. Shotgun metabolomic approach based on mass spectrometry for hepatic mitochondria of mice under arsenic exposure.

    PubMed

    García-Sevillano, M A; García-Barrera, T; Navarro, F; Montero-Lobato, Z; Gómez-Ariza, J L

    2015-04-01

    Mass spectrometry (MS)-based toxicometabolomics requires analytical approaches for obtaining unbiased metabolic profiles. The present work explores the general application of direct infusion MS using a high mass resolution analyzer (a hybrid systems triple quadrupole-time-of-flight) and a complementary gas chromatography-MS analysis to mitochondria extracts from mouse hepatic cells, emphasizing on mitochondria isolation from hepatic cells with a commercial kit, sample treatment after cell lysis, comprehensive metabolomic analysis and pattern recognition from metabolic profiles. Finally, the metabolomic platform was successfully checked on a case-study based on the exposure experiment of mice Mus musculus to inorganic arsenic during 12 days. Endogenous metabolites alterations were recognized by partial least squares-discriminant analysis. Subsequently, metabolites were identified by combining MS/MS analysis and metabolomics databases. This work reports for the first time the effects of As-exposure on hepatic mitochondria metabolic pathways based on MS, and reveals disturbances in Krebs cycle, β-oxidation pathway, amino acids degradation and perturbations in creatine levels. This non-target analysis provides extensive metabolic information from mitochondrial organelle, which could be applied to toxicology, pharmacology and clinical studies.

  12. The Recent Developments in Sample Preparation for Mass Spectrometry-Based Metabolomics.

    PubMed

    Gong, Zhi-Gang; Hu, Jing; Wu, Xi; Xu, Yong-Jiang

    2017-07-04

    Metabolomics is a critical member in systems biology. Although great progress has been achieved in metabolomics, there are still some problems in sample preparation, data processing and data interpretation. In this review, we intend to explore the roles, challenges and trends in sample preparation for mass spectrometry- (MS-) based metabolomics. The newly emerged sample preparation methods were also critically examined, including laser microdissection, in vivo sampling, dried blood spot, microwave, ultrasound and enzyme-assisted extraction, as well as microextraction techniques. Finally, we provide some conclusions and perspectives for sample preparation in MS-based metabolomics.

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

    PubMed

    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.

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

    PubMed Central

    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. PMID:26636104

  15. Metabolomics: A potential way to know the role of vitamin D on multiple sclerosis.

    PubMed

    Luque-Córdoba, Diego; Luque de Castro, María D

    2017-03-20

    The literature about the influence of vitamin D on multiple sclerosis (MS) is very controversial, possibly as a result of the way through which the research on the subject has been conducted. The studies developed so far have been focused exclusively on gene expression: the effect of a given vitamin D metabolite on target receptors. The influence of the vitamin D status (either natural or after supplementation) on MS has been studied by measurement of the 25 monohydroxylated metabolite (also known as circulating form), despite the 1,25 dihydroxylated metabolite is considered the active form. In the light of the multiple metabolic pathways in which both forms of vitamin D (D 2 and D 3 ) are involved, monitoring of the metabolites is crucial to know the activity of the target enzymes as a function of both the state of the MS patient and the clinical treatment applied. The study of metabolomics aspects is here proposed to clarify the present controversy. In "omics" terms, our proposal is to take profit from up-stream information-thus is, from metabolomics to genomics-with a potential subsequent step to systems biology, if required. Copyright © 2016 Elsevier B.V. All rights reserved.

  16. Brain and blood metabolite signatures of pathology and progression in Alzheimer disease: A targeted metabolomics study.

    PubMed

    Varma, Vijay R; Oommen, Anup M; Varma, Sudhir; Casanova, Ramon; An, Yang; Andrews, Ryan M; O'Brien, Richard; Pletnikova, Olga; Troncoso, Juan C; Toledo, Jon; Baillie, Rebecca; Arnold, Matthias; Kastenmueller, Gabi; Nho, Kwangsik; Doraiswamy, P Murali; Saykin, Andrew J; Kaddurah-Daouk, Rima; Legido-Quigley, Cristina; Thambisetty, Madhav

    2018-01-01

    The metabolic basis of Alzheimer disease (AD) is poorly understood, and the relationships between systemic abnormalities in metabolism and AD pathogenesis are unclear. Understanding how global perturbations in metabolism are related to severity of AD neuropathology and the eventual expression of AD symptoms in at-risk individuals is critical to developing effective disease-modifying treatments. In this study, we undertook parallel metabolomics analyses in both the brain and blood to identify systemic correlates of neuropathology and their associations with prodromal and preclinical measures of AD progression. Quantitative and targeted metabolomics (Biocrates AbsoluteIDQ [identification and quantification] p180) assays were performed on brain tissue samples from the autopsy cohort of the Baltimore Longitudinal Study of Aging (BLSA) (N = 44, mean age = 81.33, % female = 36.36) from AD (N = 15), control (CN; N = 14), and "asymptomatic Alzheimer's disease" (ASYMAD, i.e., individuals with significant AD pathology but no cognitive impairment during life; N = 15) participants. Using machine-learning methods, we identified a panel of 26 metabolites from two main classes-sphingolipids and glycerophospholipids-that discriminated AD and CN samples with accuracy, sensitivity, and specificity of 83.33%, 86.67%, and 80%, respectively. We then assayed these 26 metabolites in serum samples from two well-characterized longitudinal cohorts representing prodromal (Alzheimer's Disease Neuroimaging Initiative [ADNI], N = 767, mean age = 75.19, % female = 42.63) and preclinical (BLSA) (N = 207, mean age = 78.68, % female = 42.63) AD, in which we tested their associations with magnetic resonance imaging (MRI) measures of AD-related brain atrophy, cerebrospinal fluid (CSF) biomarkers of AD pathology, risk of conversion to incident AD, and trajectories of cognitive performance. We developed an integrated blood and brain endophenotype score that summarized the relative importance of each

  17. Brain and blood metabolite signatures of pathology and progression in Alzheimer disease: A targeted metabolomics study

    PubMed Central

    Oommen, Anup M.; Varma, Sudhir; Casanova, Ramon; An, Yang; O’Brien, Richard; Pletnikova, Olga; Kastenmueller, Gabi; Doraiswamy, P. Murali; Kaddurah-Daouk, Rima; Thambisetty, Madhav

    2018-01-01

    Background The metabolic basis of Alzheimer disease (AD) is poorly understood, and the relationships between systemic abnormalities in metabolism and AD pathogenesis are unclear. Understanding how global perturbations in metabolism are related to severity of AD neuropathology and the eventual expression of AD symptoms in at-risk individuals is critical to developing effective disease-modifying treatments. In this study, we undertook parallel metabolomics analyses in both the brain and blood to identify systemic correlates of neuropathology and their associations with prodromal and preclinical measures of AD progression. Methods and findings Quantitative and targeted metabolomics (Biocrates AbsoluteIDQ [identification and quantification] p180) assays were performed on brain tissue samples from the autopsy cohort of the Baltimore Longitudinal Study of Aging (BLSA) (N = 44, mean age = 81.33, % female = 36.36) from AD (N = 15), control (CN; N = 14), and “asymptomatic Alzheimer’s disease” (ASYMAD, i.e., individuals with significant AD pathology but no cognitive impairment during life; N = 15) participants. Using machine-learning methods, we identified a panel of 26 metabolites from two main classes—sphingolipids and glycerophospholipids—that discriminated AD and CN samples with accuracy, sensitivity, and specificity of 83.33%, 86.67%, and 80%, respectively. We then assayed these 26 metabolites in serum samples from two well-characterized longitudinal cohorts representing prodromal (Alzheimer’s Disease Neuroimaging Initiative [ADNI], N = 767, mean age = 75.19, % female = 42.63) and preclinical (BLSA) (N = 207, mean age = 78.68, % female = 42.63) AD, in which we tested their associations with magnetic resonance imaging (MRI) measures of AD-related brain atrophy, cerebrospinal fluid (CSF) biomarkers of AD pathology, risk of conversion to incident AD, and trajectories of cognitive performance. We developed an integrated blood and brain endophenotype score that

  18. NMR-based Metabolomics Applications in Biological and Environmental Science

    EPA Science Inventory

    As a complimentary tool to other omics platforms, metabolomics is increasingly being used bybiologists to study the dynamic response of biological systems (cells, tissues, or wholeorganisms) under diverse physiological or pathological conditions. Metabolomics deals with the quali...

  19. Target and Tissue Selectivity Prediction by Integrated Mechanistic Pharmacokinetic-Target Binding and Quantitative Structure Activity Modeling.

    PubMed

    Vlot, Anna H C; de Witte, Wilhelmus E A; Danhof, Meindert; van der Graaf, Piet H; van Westen, Gerard J P; de Lange, Elizabeth C M

    2017-12-04

    Selectivity is an important attribute of effective and safe drugs, and prediction of in vivo target and tissue selectivity would likely improve drug development success rates. However, a lack of understanding of the underlying (pharmacological) mechanisms and availability of directly applicable predictive methods complicates the prediction of selectivity. We explore the value of combining physiologically based pharmacokinetic (PBPK) modeling with quantitative structure-activity relationship (QSAR) modeling to predict the influence of the target dissociation constant (K D ) and the target dissociation rate constant on target and tissue selectivity. The K D values of CB1 ligands in the ChEMBL database are predicted by QSAR random forest (RF) modeling for the CB1 receptor and known off-targets (TRPV1, mGlu5, 5-HT1a). Of these CB1 ligands, rimonabant, CP-55940, and Δ 8 -tetrahydrocanabinol, one of the active ingredients of cannabis, were selected for simulations of target occupancy for CB1, TRPV1, mGlu5, and 5-HT1a in three brain regions, to illustrate the principles of the combined PBPK-QSAR modeling. Our combined PBPK and target binding modeling demonstrated that the optimal values of the K D and k off for target and tissue selectivity were dependent on target concentration and tissue distribution kinetics. Interestingly, if the target concentration is high and the perfusion of the target site is low, the optimal K D value is often not the lowest K D value, suggesting that optimization towards high drug-target affinity can decrease the benefit-risk ratio. The presented integrative structure-pharmacokinetic-pharmacodynamic modeling provides an improved understanding of tissue and target selectivity.

  20. QCScreen: a software tool for data quality control in LC-HRMS based metabolomics.

    PubMed

    Simader, Alexandra Maria; Kluger, Bernhard; Neumann, Nora Katharina Nicole; Bueschl, Christoph; Lemmens, Marc; Lirk, Gerald; Krska, Rudolf; Schuhmacher, Rainer

    2015-10-24

    Metabolomics experiments often comprise large numbers of biological samples resulting in huge amounts of data. This data needs to be inspected for plausibility before data evaluation to detect putative sources of error e.g. retention time or mass accuracy shifts. Especially in liquid chromatography-high resolution mass spectrometry (LC-HRMS) based metabolomics research, proper quality control checks (e.g. for precision, signal drifts or offsets) are crucial prerequisites to achieve reliable and comparable results within and across experimental measurement sequences. Software tools can support this process. The software tool QCScreen was developed to offer a quick and easy data quality check of LC-HRMS derived data. It allows a flexible investigation and comparison of basic quality-related parameters within user-defined target features and the possibility to automatically evaluate multiple sample types within or across different measurement sequences in a short time. It offers a user-friendly interface that allows an easy selection of processing steps and parameter settings. The generated results include a coloured overview plot of data quality across all analysed samples and targets and, in addition, detailed illustrations of the stability and precision of the chromatographic separation, the mass accuracy and the detector sensitivity. The use of QCScreen is demonstrated with experimental data from metabolomics experiments using selected standard compounds in pure solvent. The application of the software identified problematic features, samples and analytical parameters and suggested which data files or compounds required closer manual inspection. QCScreen is an open source software tool which provides a useful basis for assessing the suitability of LC-HRMS data prior to time consuming, detailed data processing and subsequent statistical analysis. It accepts the generic mzXML format and thus can be used with many different LC-HRMS platforms to process both multiple

  1. A prominent role for the CBF cold response pathway in configuring the low-temperature metabolome of Arabidopsis

    PubMed Central

    Cook, Daniel; Fowler, Sarah; Fiehn, Oliver; Thomashow, Michael F.

    2004-01-01

    The Arabidopsis CBF cold response pathway has a central role in cold acclimation, the process whereby plants increase in freezing tolerance in response to low nonfreezing temperatures. Here we examined the changes that occur in the Arabidopsis metabolome in response to low temperature and assessed the role of the CBF cold response pathway in bringing about these modifications. Of 434 metabolites monitored by GC-time-of-flight MS, 325 (75%) were found to increase in Arabidopsis Wassilewskija-2 (Ws-2) plants in response to low temperature. Of these 325 metabolites, 256 (79%) also increased in nonacclimated Ws-2 plants in response to overexpression of C-repeat/dehydration responsive element-binding factor (CBF)3. Extensive cold-induced changes also occurred in the metabolome of Arabidopsis Cape Verde Islands-1 (Cvi-1) plants, which were found to be less freezing tolerant than Ws-2 plants. However, low-temperature-induced expression of CBF1, CBF2, CBF3, and CBF-targeted genes was much lower in Cvi-1 than in Ws-2 plants, and the low-temperature metabolome of Cvi-1 plants was depleted in metabolites affected by CBF3 overexpression. Taken together, the results indicate that the metabolome of Arabidopsis is extensively reconfigured in response to low temperature, and that the CBF cold response pathway has a prominent role in this process. PMID:15383661

  2. A metabolomics-based method for studying the effect of yfcC gene in Escherichia coli on metabolism.

    PubMed

    Wang, Xiyue; Xie, Yuping; Gao, Peng; Zhang, Sufang; Tan, Haidong; Yang, Fengxu; Lian, Rongwei; Tian, Jing; Xu, Guowang

    2014-04-15

    Metabolomics is a potent tool to assist in identifying the function of unknown genes through analysis of metabolite changes in the context of varied genetic backgrounds. However, the availability of a universal unbiased profiling analysis is still a big challenge. In this study, we report an optimized metabolic profiling method based on gas chromatography-mass spectrometry for Escherichia coli. It was found that physiological saline at -80°C could ensure satisfied metabolic quenching with less metabolite leakage. A solution of methanol/water (21:79, v/v) was proved to be efficient for intracellular metabolite extraction. This method was applied to investigate the metabolome difference among wild-type E. coli, its yfcC deletion, and overexpression mutants. Statistical and bioinformatic analysis of the metabolic profiling data indicated that the expression of yfcC potentially affected the metabolism of glyoxylate shunt. This finding was further validated by real-time quantitative polymerase chain reactions showing that expression of aceA and aceB, the key genes in glyoxylate shunt, was upregulated by yfcC. This study exemplifies the robustness of the proposed metabolic profiling analysis strategy and its potential roles in investigating unknown gene functions in view of metabolome difference. Copyright © 2014 Elsevier Inc. All rights reserved.

  3. Comparison of quantitative PCR assays for Escherichia coli targeting ribosomal RNA and single copy genes

    EPA Science Inventory

    Aims: Compare specificity and sensitivity of quantitative PCR (qPCR) assays targeting single and multi-copy gene regions of Escherichia coli. Methods and Results: A previously reported assay targeting the uidA gene (uidA405) was used as the basis for comparing the taxono...

  4. The Karlsruhe Metabolomics and Nutrition (KarMeN) Study: Protocol and Methods of a Cross-Sectional Study to Characterize the Metabolome of Healthy Men and Women

    PubMed Central

    Kriebel, Anita; Dörr, Claudia; Bandt, Susanne; Rist, Manuela; Roth, Alexander; Hummel, Eva; Kulling, Sabine; Hoffmann, Ingrid; Watzl, Bernhard

    2016-01-01

    Background The human metabolome is influenced by various intrinsic and extrinsic factors. A precondition to identify such biomarkers is the comprehensive understanding of the composition and variability of the metabolome of healthy humans. Sample handling aspects have an important impact on the composition of the metabolome; therefore, it is crucial for any metabolomics study to standardize protocols on sample collection, preanalytical sample handling, storage, and analytics to keep the nonbiological variability as low as possible. Objective The main objective of the KarMeN study is to analyze the human metabolome in blood and urine by targeted and untargeted metabolite profiling (gas chromatography-mass spectrometry [GC-MS], GC×GC-MS, liquid chromatography-mass spectrometry [LC-MS/MS], and1H nuclear magnetic resonance [NMR] spectroscopy) and to determine the impact of sex, age, body composition, diet, and physical activity on metabolite profiles of healthy women and men. Here, we report the outline of the study protocol with special regard to all aspects that should be considered in studies applying metabolomics. Methods Healthy men and women, aged 18 years or older, were recruited. In addition to a number of anthropometric (height, weight, body mass index, waist circumference, body composition), clinical (blood pressure, electrocardiogram, blood and urine clinical chemistry) and functional parameters (lung function, arterial stiffness), resting metabolic rate, physical activity, fitness, and dietary intake were assessed, and 24-hour urine, fasting spot urine, and plasma samples were collected. Standard operating procedures were established for all steps of the study design. Using different analytical techniques (LC-MS, GC×GC-MS,1H NMR spectroscopy), metabolite profiles of urine and plasma were determined. Data will be analyzed using univariate and multivariate as well as predictive modeling methods. Results The project was funded in 2011 and enrollment was

  5. Metabolomics Based Profiling of Dexamethasone Side Effects in Rats

    PubMed Central

    Malkawi, Abeer K.; Alzoubi, Karem H.; Jacob, Minnie; Matic, Goran; Ali, Asmaa; Al Faraj, Achraf; Almuhanna, Falah; Dasouki, Majed; Abdel Rahman, Anas M.

    2018-01-01

    Dexamethasone (Dex) is a synthetic glucocorticoid that has anti-inflammatory and immunosuppressant effects and is used in several conditions such as asthma and severe allergy. Patients receiving Dex, either at a high dose or for a long time, might develop several side effects such as hyperglycemia, weight change, or osteoporosis due to its in vivo non-selectivity. Herein, we used liquid chromatography-tandem mass spectrometry-based comprehensive targeted metabolomic profiling as well as radiographic imaging techniques to study the side effects of Dex treatment in rats. The Dex-treated rats suffered from a ∼20% reduction in weight gain, hyperglycemia (145 mg/dL), changes in serum lipids, and reduction in total serum alkaline phosphatase (ALP) (∼600 IU/L). Also, compared to controls, Dex-treated rats showed a distinctive metabolomics profile. In particular, serum amino acids metabolism showed six-fold reduction in phenylalanine, lysine, and arginine levels and upregulation of tyrosine and hydroxyproline reflecting perturbations in gluconeogenesis and protein catabolism which together lead to weight loss and abnormal bone metabolism. Sorbitol level was markedly elevated secondary to hyperglycemia and reflecting activation of the polyol metabolism pathway causing a decrease in the availability of reducing molecules (glutathione, NADPH, NAD+). Overexpression of succinylacetone (4,6-dioxoheptanoic acid) suggests a novel inhibitory effect of Dex on hepatic fumarylacetoacetate hydrolase. The acylcarnitines, mainly the very long chain species (C12, C14:1, C18:1) were significantly increased after Dex treatment which reflects degradation of the adipose tissue. In conclusion, long-term Dex therapy in rats is associated with a distinctive metabolic profile which correlates with its side effects. Therefore, metabolomics based profiling may predict Dex treatment-related side effects and may offer possible novel therapeutic interventions. PMID:29503615

  6. Metabolomics Based Profiling of Dexamethasone Side Effects in Rats.

    PubMed

    Malkawi, Abeer K; Alzoubi, Karem H; Jacob, Minnie; Matic, Goran; Ali, Asmaa; Al Faraj, Achraf; Almuhanna, Falah; Dasouki, Majed; Abdel Rahman, Anas M

    2018-01-01

    Dexamethasone (Dex) is a synthetic glucocorticoid that has anti-inflammatory and immunosuppressant effects and is used in several conditions such as asthma and severe allergy. Patients receiving Dex, either at a high dose or for a long time, might develop several side effects such as hyperglycemia, weight change, or osteoporosis due to its in vivo non-selectivity. Herein, we used liquid chromatography-tandem mass spectrometry-based comprehensive targeted metabolomic profiling as well as radiographic imaging techniques to study the side effects of Dex treatment in rats. The Dex-treated rats suffered from a ∼20% reduction in weight gain, hyperglycemia (145 mg/dL), changes in serum lipids, and reduction in total serum alkaline phosphatase (ALP) (∼600 IU/L). Also, compared to controls, Dex-treated rats showed a distinctive metabolomics profile. In particular, serum amino acids metabolism showed six-fold reduction in phenylalanine, lysine, and arginine levels and upregulation of tyrosine and hydroxyproline reflecting perturbations in gluconeogenesis and protein catabolism which together lead to weight loss and abnormal bone metabolism. Sorbitol level was markedly elevated secondary to hyperglycemia and reflecting activation of the polyol metabolism pathway causing a decrease in the availability of reducing molecules (glutathione, NADPH, NAD + ). Overexpression of succinylacetone (4,6-dioxoheptanoic acid) suggests a novel inhibitory effect of Dex on hepatic fumarylacetoacetate hydrolase. The acylcarnitines, mainly the very long chain species (C12, C14:1, C18:1) were significantly increased after Dex treatment which reflects degradation of the adipose tissue. In conclusion, long-term Dex therapy in rats is associated with a distinctive metabolic profile which correlates with its side effects. Therefore, metabolomics based profiling may predict Dex treatment-related side effects and may offer possible novel therapeutic interventions.

  7. Application of a Smartphone Metabolomics Platform to the Authentication of Schisandra sinensis.

    PubMed

    Kwon, Hyuk Nam; Phan, Hong-Duc; Xu, Wen Jun; Ko, Yoon-Joo; Park, Sunghyouk

    2016-05-01

    Herbal medicines have been used for a long time all around the world. Since the quality of herbal preparations depends on the source of herbal materials, there has been a strong need to develop methods to correctly identify the origin of materials. To develop a smartphone metabolomics platform as a simpler and low-cost alternative for the identification of herbal material source. Schisandra sinensis extracts from Korea and China were prepared. The visible spectra of all samples were measured by a smartphone spectrometer platform. This platform included all the necessary measures built-in for the metabolomics research: data acquisition, processing, chemometric analysis and visualisation of the results. The result of the smartphone metabolomics platform was compared to that of NMR-based metabolomics, suggesting the feasibility of smartphone platform in metabolomics research. The smartphone metabolomics platform gave similar results to the NMR method, showing good separation between Korean and Chinese materials and correct predictability for all test samples. With its accuracy and advantages of affordability, user-friendliness, and portability, the smartphone metabolomics platform could be applied to the authentication of other medicinal plants. Copyright © 2016 John Wiley & Sons, Ltd. Copyright © 2016 John Wiley & Sons, Ltd.

  8. Quantitative imaging of protein targets in the human brain with PET

    NASA Astrophysics Data System (ADS)

    Gunn, Roger N.; Slifstein, Mark; Searle, Graham E.; Price, Julie C.

    2015-11-01

    PET imaging of proteins in the human brain with high affinity radiolabelled molecules has a history stretching back over 30 years. During this period the portfolio of protein targets that can be imaged has increased significantly through successes in radioligand discovery and development. This portfolio now spans six major categories of proteins; G-protein coupled receptors, membrane transporters, ligand gated ion channels, enzymes, misfolded proteins and tryptophan-rich sensory proteins. In parallel to these achievements in radiochemical sciences there have also been significant advances in the quantitative analysis and interpretation of the imaging data including the development of methods for image registration, image segmentation, tracer compartmental modeling, reference tissue kinetic analysis and partial volume correction. In this review, we analyze the activity of the field around each of the protein targets in order to give a perspective on the historical focus and the possible future trajectory of the field. The important neurobiology and pharmacology is introduced for each of the six protein classes and we present established radioligands for each that have successfully transitioned to quantitative imaging in humans. We present a standard quantitative analysis workflow for these radioligands which takes the dynamic PET data, associated blood and anatomical MRI data as the inputs to a series of image processing and bio-mathematical modeling steps before outputting the outcome measure of interest on either a regional or parametric image basis. The quantitative outcome measures are then used in a range of different imaging studies including tracer discovery and development studies, cross sectional studies, classification studies, intervention studies and longitudinal studies. Finally we consider some of the confounds, challenges and subtleties that arise in practice when trying to quantify and interpret PET neuroimaging data including motion artifacts

  9. Novel Applications of Metabolomics in Personalized Medicine: A Mini-Review.

    PubMed

    Li, Bingbing; He, Xuyun; Jia, Wei; Li, Houkai

    2017-07-13

    Interindividual variability in drug responses and disease susceptibility is common in the clinic. Currently, personalized medicine is highly valued, the idea being to prescribe the right medicine to the right patient. Metabolomics has been increasingly applied in evaluating the therapeutic outcomes of clinical drugs by correlating the baseline metabolic profiles of patients with their responses, i.e., pharmacometabonomics, as well as prediction of disease susceptibility among population in advance, i.e., patient stratification. The accelerated advance in metabolomics technology pinpoints the huge potential of its application in personalized medicine. In current review, we discussed the novel applications of metabolomics with typical examples in evaluating drug therapy and patient stratification, and underlined the potential of metabolomics in personalized medicine in the future.

  10. [Using (1)H-nuclear magnetic resonance metabolomics and gene ontology to establish pathological staging model for esophageal cancer patients].

    PubMed

    Chen, X; Wang, K; Chen, W; Jiang, H; Deng, P C; Li, Z J; Peng, J; Zhou, Z Y; Yang, H; Huang, G X; Zeng, J

    2016-07-01

    By combining the metabolomics and computational biology, to explore the relationship between metabolic phenotype and pathological stage in esophageal cancer patients, to find the mechanism of metabolic network disturbance and develop a new method for fast preoperative clinical staging. A prospective cohort study (from April 2013 to January 2016) was conducted. The preoperative patients from Sichuan Provincial People's Hospital, who were diagnosed with esophageal cancer from May 2013 to April 2014 were included, and their serum samples were collected to detect (1)H-nuclear magnetic resonance (NMR) metabolomics for the purpose of drawing the metabolic fingerprinting in different stages of patients with esophageal cancer. The data were processed with these methods-principal components analysis: partial least squares regression and support vector machine, for the exploration of the enzyme-gene network regulatory mechanism in abnormal esophageal cancer metabolic network regulation and to build the quantitative prediction model of esophageal cancer staging in the end. All data were processed on high-performance computing platforms Matalab. The comparison of data had used Wilcoxon test, variance analysis, χ(2) test and Fisher exact test. Twenty patients with different stages of esophageal cancer were included; and their serum metabolic fingerprinting could differentiate different tumor stages. There were no difference among the five teams in the age (F=1.086, P>0.05), the body mass index (F=1.035, P>0.05), the distance from the incisors to tumor (F=1.078, P>0.05). Among the patients with different TNM stages, there was a significant difference in plasma metabolome. Compared to ⅡB, ⅢA, Ⅳstage patients, increased levels of butanone, ethanol amine, homocysteine, hydroxy acids and estriol, together with decreased levels of glycoprotein, creatine, choline, isobutyricacid, alanine, leucine, valine, were observed inⅠB, ⅡA stage patients. Four metabolic markers

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

    PubMed

    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.

  12. Integrated metabolomic profiling of hepatocellular carcinoma in hepatitis C cirrhosis through GC/MS and UPLC/MS-MS.

    PubMed

    Fitian, Asem I; Nelson, David R; Liu, Chen; Xu, Yiling; Ararat, Miguel; Cabrera, Roniel

    2014-10-01

    The metabolic pathway disturbances associated with hepatocellular carcinoma (HCC) remain unsatisfactorily characterized. Determination of the metabolic alterations associated with the presence of HCC can improve our understanding of the pathophysiology of this cancer and may provide opportunities for improved disease monitoring of patients at risk for HCC development. To characterize the global metabolic alterations associated with HCC arising from hepatitis C (HCV)-associated cirrhosis using an integrated non-targeted metabolomics methodology employing both gas chromatography/mass spectrometry (GC/MS) and ultrahigh-performance liquid chromatography/electrospray ionization tandem mass spectrometry (UPLC/MS-MS). The global serum metabolomes of 30 HCC patients, 27 hepatitis C cirrhosis disease controls and 30 healthy volunteers were characterized using a metabolomics approach that combined two metabolomics platforms, GC/MS and UPLC/MS-MS. Random forest, multivariate statistics and receiver operator characteristic analysis were performed to identify the most significantly altered metabolites in HCC patients vs. HCV-cirrhosis controls and which therefore exhibited a close association with the presence of HCC. Elevated 12-hydroxyeicosatetraenoic acid (12-HETE), 15-HETE, sphingosine, γ-glutamyl oxidative stress-associated metabolites, xanthine, amino acids serine, glycine and aspartate, and acylcarnitines were strongly associated with the presence of HCC. Elevations in bile acids and dicarboxylic acids were highly correlated with cirrhosis. Integrated metabolomic profiling through GC/MS and UPLC/MS-MS identified global metabolic disturbances in HCC and HCV-cirrhosis. Aberrant amino acid biosynthesis, cell turnover regulation, reactive oxygen species neutralization and eicosanoid pathways may be hallmarks of HCC. Aberrant dicarboxylic acid metabolism, enhanced bile acid metabolism and elevations in fibrinogen cleavage peptides may be signatures of cirrhosis. © 2014 John

  13. Systematic analysis of the polyphenol metabolome using the Phenol-Explorer database.

    PubMed

    Rothwell, Joseph A; Urpi-Sarda, Mireia; Boto-Ordoñez, Maria; Llorach, Rafael; Farran-Codina, Andreu; Barupal, Dinesh Kumar; Neveu, Vanessa; Manach, Claudine; Andres-Lacueva, Cristina; Scalbert, Augustin

    2016-01-01

    The Phenol-Explorer web database details 383 polyphenol metabolites identified in human and animal biofluids from 221 publications. Here, we exploit these data to characterize and visualize the polyphenol metabolome, the set of all metabolites derived from phenolic food components. Qualitative and quantitative data on 383 polyphenol metabolites as described in 424 human and animal intervention studies were systematically analyzed. Of these metabolites, 301 were identified without prior enzymatic hydrolysis of biofluids, and included glucuronide and sulfate esters, glycosides, aglycones, and O-methyl ethers. Around one-third of these compounds are also known as food constituents and corresponded to polyphenols absorbed without further metabolism. Many ring-cleavage metabolites formed by gut microbiota were noted, mostly derived from hydroxycinnamates, flavanols, and flavonols. Median maximum plasma concentrations (C(max)) of all human metabolites were 0.09 and 0.32 μM when consumed from foods or dietary supplements, respectively. Median time to reach maximum plasma concentration in humans (T(max)) was 2.18 h. These data show the complexity of the polyphenol metabolome and the need to take into account biotransformations to understand in vivo bioactivities and the role of dietary polyphenols in health and disease. © 2015 The Authors. Molecular Nutrition & Food Research published by Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

  14. Targeted Metabolomics Reveals a Protective Role for Basal PPARα in Cholestasis Induced by α-Naphthylisothiocyanate.

    PubMed

    Dai, Manyun; Hua, Huiying; Lin, Hante; Xu, Gangming; Hu, Xiaowei; Li, Fei; Gonzalez, Frank J; Liu, Aiming; Yang, Julin

    2018-04-06

    α-Naphthylisothiocyanate (ANIT) is an experimental agent used to induce intrahepatic cholestasis. The Ppara-null mouse line is widely employed to explore the physiological and pathological roles of PPARα. However, little is known about how PPARα influences the hepatotoxicity of ANIT. In the present study, wild-type and Ppara-null mice were orally treated with ANIT to induce cholestasis. The serum metabolome of wild-type mice segregated from that of the Ppara-null mice, driven by changes of bile acid (BA) metabolites. Alkaline phosphatase and total BAs were elevated preferentially in Ppara-null mice, which correlated with changes in Cyp7a1, Cyp8b1, Mrp3, Cyp3a11, Cyp2b10, Ugt1a2, and Ugt1a5 genes and showed cross-talk between basal PPARα and potentially adaptive pathways. Il6, Tnfa, and target genes in the STAT3 pathway ( Socs3, Fga, Fgb, and Fgg) were up-regulated in Ppara-null mice but not in wild-type mice. The JNK pathway was activated in both mouse lines, while NF-κB and STAT3 were activated only in Ppara-null mice. These data suggest protection against cholestasis by basal PPARα involves regulation of BA metabolism and inhibition of NF-κB/STAT3 signaling. Considering studies on the protective effects of both basal and activated PPARα, caution should be exercised when one attempts to draw conclusions in which the PPARα is modified by genetic manipulation, fasting, or activation in pharmacological and toxicological studies.

  15. Metabolomic profiling in perinatal asphyxia: a promising new field.

    PubMed

    Denihan, Niamh M; Boylan, Geraldine B; Murray, Deirdre M

    2015-01-01

    Metabolomics, the latest "omic" technology, is defined as the comprehensive study of all low molecular weight biochemicals, "metabolites" present in an organism. As a systems biology approach, metabolomics has huge potential to progress our understanding of perinatal asphyxia and neonatal hypoxic-ischaemic encephalopathy, by uniquely detecting rapid biochemical pathway alterations in response to the hypoxic environment. The study of metabolomic biomarkers in the immediate neonatal period is not a trivial task and requires a number of specific considerations, unique to this disease and population. Recruiting a clearly defined cohort requires standardised multicentre recruitment with broad inclusion criteria and the participation of a range of multidisciplinary staff. Minimally invasive biospecimen collection is a priority for biomarker discovery. Umbilical cord blood presents an ideal medium as large volumes can be easily extracted and stored and the sample is not confounded by postnatal disease progression. Pristine biobanking and phenotyping are essential to ensure the validity of metabolomic findings. This paper provides an overview of the current state of the art in the field of metabolomics in perinatal asphyxia and neonatal hypoxic-ischaemic encephalopathy. We detail the considerations required to ensure high quality sampling and analysis, to support scientific progression in this important field.

  16. Metabolomic Profiling in Perinatal Asphyxia: A Promising New Field

    PubMed Central

    Denihan, Niamh M.; Boylan, Geraldine B.; Murray, Deirdre M.

    2015-01-01

    Metabolomics, the latest “omic” technology, is defined as the comprehensive study of all low molecular weight biochemicals, “metabolites” present in an organism. As a systems biology approach, metabolomics has huge potential to progress our understanding of perinatal asphyxia and neonatal hypoxic-ischaemic encephalopathy, by uniquely detecting rapid biochemical pathway alterations in response to the hypoxic environment. The study of metabolomic biomarkers in the immediate neonatal period is not a trivial task and requires a number of specific considerations, unique to this disease and population. Recruiting a clearly defined cohort requires standardised multicentre recruitment with broad inclusion criteria and the participation of a range of multidisciplinary staff. Minimally invasive biospecimen collection is a priority for biomarker discovery. Umbilical cord blood presents an ideal medium as large volumes can be easily extracted and stored and the sample is not confounded by postnatal disease progression. Pristine biobanking and phenotyping are essential to ensure the validity of metabolomic findings. This paper provides an overview of the current state of the art in the field of metabolomics in perinatal asphyxia and neonatal hypoxic-ischaemic encephalopathy. We detail the considerations required to ensure high quality sampling and analysis, to support scientific progression in this important field. PMID:25802843

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

    PubMed

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

    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(-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. Copyright 2009 Elsevier B.V. All rights reserved.

  18. Cultivar Determination of Ricinus communis via the Metabolome: a Proof of Concept Investigation

    DTIC Science & Technology

    2009-08-01

    metabolome found in an organism is the result of the interaction between the organisms’ genome and the environment. Metabolomics has been applied to...Cultivar Determination of Ricinus communis via the Metabolome : a Proof of Concept Investigation Simon P. B. Ovenden, Benjamin R. Gordon¹, Christina...appropriateness of studying the metabolome of Ricinus communis for cultivar and provenance determination. Seeds from fourteen R. communis specimens (a total of 56

  19. The Human Serum Metabolome of Vitamin B-12 Deficiency and Repletion, and Associations with Neurological Function in Elderly Adults.

    PubMed

    Brito, Alex; Grapov, Dmitry; Fahrmann, Johannes; Harvey, Danielle; Green, Ralph; Miller, Joshua W; Fedosov, Sergey N; Shahab-Ferdows, Setareh; Hampel, Daniela; Pedersen, Theresa L; Fiehn, Oliver; Newman, John W; Uauy, Ricardo; Allen, Lindsay H

    2017-08-09

    Background: The specific metabolomic perturbations that occur in vitamin B-12 deficiency, and their associations with neurological function, are not well characterized. Objective: We sought to characterize the human serum metabolome in subclinical vitamin B-12 deficiency and repletion. Methods: A before-and-after treatment study provided 1 injection of 10 mg vitamin B-12 (with 100 mg pyridoxine and 100 mg thiamin) to 27 community-dwelling elderly Chileans (∼74 y old) with vitamin B-12 deficiency, as evaluated with serum vitamin B-12, total plasma homocysteine (tHcy), methylmalonic acid (MMA), and holotranscobalamin. The combined indicator of vitamin B-12 status (cB-12) was computed. Targeted metabolites [166 acylcarnitines, amino acids, sugars, glycerophospholipids, and sphingolipids (liquid chromatography-tandem mass spectrometry)], and untargeted metabolites [247 chemical entities (gas chromatography time-of-flight mass spectrometry)] were measured at baseline and 4 mo after treatment. A peripheral nerve score was developed. Differences before and after treatment were examined. For targeted metabolomics, the data from 18 individuals with adequate vitamin B-12 status (selected from the same population) were added to the before-and-after treatment data set. Network visualizations and metabolic pathways are illustrated. Results: The injection increased serum vitamin B-12, holotranscobalamin, and cB-12 ( P < 0.001), and reduced tHcy and serum MMA ( P < 0.001). Metabolomic changes from before to after treatment included increases ( P < 0.001) in acylcarnitines, plasmalogens, and other phospholipids, whereas proline and other intermediaries of one-carbon metabolism-that is, methionine and cysteine-were reduced ( P < 0.001). Direct significant correlations ( P < 0.05 after the false discovery rate procedure) were identified between acylcarnitines, plasmalogens, phospholipids, lyso-phospholipids, and sphingomyelins compared with vitamin B-12 status and nerve function

  20. Metabolomic Elucidation of the Effects of Curcumin on Fibroblast-Like Synoviocytes in Rheumatoid Arthritis

    PubMed Central

    Hwang, Jiwon; Kim, Jungyeon; Lee, You Sun; Koh, Eun-Mi; Kim, Kyoung Heon; Cha, Hoon-Suk

    2015-01-01

    Rheumatoid arthritis (RA) is a chronic systemic inflammatory disease characterized by synovial inflammation and joint disability. Curcumin is known to be effective in ameliorating joint inflammation in RA. To obtain new insights into the effect of curcumin on primary fibroblast-like synoviocytes (FLS, N = 3), which are key effector cells in RA, we employed gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS)-based metabolomics. Metabolomic profiling of tumor necrosis factor (TNF)-α-stimulated and curcumin-treated FLS was performed using GC/TOF-MS in conjunction with univariate and multivariate statistical analyses. A total of 119 metabolites were identified. Metabolomic analysis revealed that metabolite profiles were clearly distinct between TNF-α-stimulated vs. the control group (not stimulated by TNF-α or curcumin). Treatment of FLS with curcumin showed that the metabolic perturbation by TNF-α could be reversed to that of the control group to a considerable extent. Curcumin-treated FLS had higher restoration of amino acid and fatty acid metabolism, as indicated by the prominent metabolic restoration of intermediates of amino acid and fatty acid metabolism, compared with that observed in TNF-α-stimulated FLS. In particular, the abundance of glycine, citrulline, arachidonic acid, and saturated fatty acids in TNF-α-stimulated FLS was restored to the control level after treatment with curcumin, suggesting that the effect of curcumin on preventing joint inflammation may be elucidated with the levels of these metabolites. Our results suggest that GC/TOF-MS-based metabolomic investigation using FLS has the potential for discovering the mechanism of action of curcumin and new targets for therapeutic drugs in RA. PMID:26716989

  1. Metabolomic Elucidation of the Effects of Curcumin on Fibroblast-Like Synoviocytes in Rheumatoid Arthritis.

    PubMed

    Ahn, Joong Kyong; Kim, Sooah; Hwang, Jiwon; Kim, Jungyeon; Lee, You Sun; Koh, Eun-Mi; Kim, Kyoung Heon; Cha, Hoon-Suk

    2015-01-01

    Rheumatoid arthritis (RA) is a chronic systemic inflammatory disease characterized by synovial inflammation and joint disability. Curcumin is known to be effective in ameliorating joint inflammation in RA. To obtain new insights into the effect of curcumin on primary fibroblast-like synoviocytes (FLS, N = 3), which are key effector cells in RA, we employed gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS)-based metabolomics. Metabolomic profiling of tumor necrosis factor (TNF)-α-stimulated and curcumin-treated FLS was performed using GC/TOF-MS in conjunction with univariate and multivariate statistical analyses. A total of 119 metabolites were identified. Metabolomic analysis revealed that metabolite profiles were clearly distinct between TNF-α-stimulated vs. the control group (not stimulated by TNF-α or curcumin). Treatment of FLS with curcumin showed that the metabolic perturbation by TNF-α could be reversed to that of the control group to a considerable extent. Curcumin-treated FLS had higher restoration of amino acid and fatty acid metabolism, as indicated by the prominent metabolic restoration of intermediates of amino acid and fatty acid metabolism, compared with that observed in TNF-α-stimulated FLS. In particular, the abundance of glycine, citrulline, arachidonic acid, and saturated fatty acids in TNF-α-stimulated FLS was restored to the control level after treatment with curcumin, suggesting that the effect of curcumin on preventing joint inflammation may be elucidated with the levels of these metabolites. Our results suggest that GC/TOF-MS-based metabolomic investigation using FLS has the potential for discovering the mechanism of action of curcumin and new targets for therapeutic drugs in RA.

  2. Nutrigenomics and metabolomics will change clinical nutrition and public health practice: insights from studies on dietary requirements for choline2

    PubMed Central

    Zeisel, Steven H

    2008-01-01

    Science is beginning to understand how genetic variation and epigenetic events alter requirements for, and responses to, nutrients (nutrigenomics). At the same time, methods for profiling almost all of the products of metabolism in a single sample of blood or urine are being developed (metabolomics). Relations between diet and nutrigenomic and metabolomic profiles and between those profiles and health have become important components of research that could change clinical practice in nutrition. Most nutrition studies assume that all persons have average dietary requirements, and the studies often do not plan for a large subset of subjects who differ in requirements for a nutrient. Large variances in responses that occur when such a population exists can result in statistical analyses that argue for a null effect. If nutrition studies could better identify responders and differentiate them from nonresponders on the basis of nutrigenomic or metabolomic profiles, the sensitivity to detect differences between groups could be greatly increased, and the resulting dietary recommendations could be appropriately targeted. It is not certain that nutrition will be the clinical specialty primarily responsible for nutrigenomics or metabolomics, because other disciplines currently dominate the development of portions of these fields. However, nutrition scientists' depth of understanding of human metabolism can be used to establish a role in the research and clinical programs that will arise from nutrigenomic and metabolomic profiling. Investments made today in training programs and in research methods could ensure a new foundation for clinical nutrition in the future. PMID:17823415

  3. Implication of Fusarium graminearum primary metabolism in its resistance to benzimidazole fungicides as revealed by 1H NMR metabolomics.

    PubMed

    Sevastos, A; Kalampokis, I F; Panagiotopoulou, A; Pelecanou, M; Aliferis, K A

    2018-06-01

    Fungal metabolomics is a field of high potential but yet largely unexploited. Focusing on plant-pathogenic fungi, no metabolomics studies exist on their resistance to fungicides, which represents a major issue that the agrochemical and agricultural sectors are facing. Fungal infections cause quantitative, but also qualitative yield losses, especially in the case of mycotoxin-producing species. The aim of the study was to correlate metabolic changes in Fusarium graminearum strains' metabolomes with their carbendazim-resistant level and discover corresponding metabolites-biomarkers, with primary focus on its primary metabolism. For this purpose, comparative 1 H NMR metabolomics was applied to a wild-type and four carbendazim-resistant Fusarium graminearum strains following or not exposure to the fungicide. Results showed an excellent discrimination between the strains based on their carbendazim-resistance following exposure to low concentration of the fungicide (2 mg L -1 ). Both genotype and fungicide treatments had a major impact on fungal metabolism. Among the signatory metabolites, a positive correlation was discovered between the content of F. graminearum strains in amino acids of the aromatic and pyruvate families, l-glutamate, l-proline, l-serine, pyroglutamate, and succinate and their carbendazim-resistance level. In contrary, their content in l-glutamine and l-threonine, had a negative correlation. Many of these metabolites play important roles in fungal physiology and responses to stresses. This work represents a proof-of-concept of the applicability of 1 H NMR metabolomics for high-throughput screening of fungal mutations leading to fungicide resistance, and the study of its biochemical basis, focusing on the involvement of primary metabolism. Results could be further exploited in programs of resistance monitoring, genetic engineering, and crop protection for combating fungal resistance to fungicides. Copyright © 2018 Elsevier Inc. All rights reserved.

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

    PubMed

    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.

  5. Diagnosis of gastroenterological diseases by metabolome analysis using gas chromatography-mass spectrometry.

    PubMed

    Yoshida, Masaru; Hatano, Naoya; Nishiumi, Shin; Irino, Yasuhiro; Izumi, Yoshihiro; Takenawa, Tadaomi; Azuma, Takeshi

    2012-01-01

    Recently, metabolome analysis has been increasingly applied to biomarker detection and disease diagnosis in medical studies. Metabolome analysis is a strategy for studying the characteristics and interactions of low molecular weight metabolites under a specific set of conditions and is performed using mass spectrometry and nuclear magnetic resonance spectroscopy. There is a strong possibility that changes in metabolite levels reflect the functional status of a cell because alterations in their levels occur downstream of DNA, RNA, and protein. Therefore, the metabolite profile of a cell is more likely to represent the current status of a cell than DNA, RNA, or protein. Thus, owing to the rapid development of mass spectrometry analytical techniques metabolome analysis is becoming an important experimental method in life sciences including the medical field. Here, we describe metabolome analysis using liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry (GC-MS), capillary electrophoresis-mass spectrometry, and matrix assisted laser desorption ionization-mass spectrometry. Then, the findings of studies about GC-MS-based metabolome analysis of gastroenterological diseases are summarized, and our research results are also introduced. Finally, we discuss the realization of disease diagnosis by metabolome analysis. The development of metabolome analysis using mass spectrometry will aid the discovery of novel biomarkers, hopefully leading to the early detection of various diseases.

  6. Effect of Antibiotics and Diet on Enterolactone Concentration and Metabolome Studied by Targeted and Nontargeted LC-MS Metabolomics.

    PubMed

    Bolvig, Anne K; Nørskov, Natalja P; Hedemann, Mette S; Foldager, Leslie; McCarthy-Sinclair, Brendan; Marco, Maria L; Lærke, Helle N; Bach Knudsen, Knud E

    2017-06-02

    High plant lignan intake is associated with a number of health benefits, possibly induced by the lignan metabolite enterolactone (ENL). The gut microbiota plays a crucial role in converting dietary lignans into ENL, and epidemiological studies have shown that use of antibiotics is associated with lower levels of ENL. Here we investigate the link between antibiotic use and lignan metabolism in pigs using LC-MS/MS. The effect of lignan intake and antibiotic use on the gut microbial community and the pig metabolome is studied by 16S rRNA sequencing and nontargeted LC-MS. Treatment with antibiotics resulted in substantially lower concentrations of ENL compared with concentrations detected in untreated animals, whereas the plasma concentrations of plant lignans were unchanged. Both diet and antibiotic treatment affected the clustering of urinary metabolites and significantly altered the proportions of taxa in the gut microbiota. Diet, but not antibiotic treatment, affected the plasma lipid profile, and a lower concentration of LDL cholesterol was observed in the pigs fed a high lignan diet. This study provides solid support for the associations between ENL concentrations and use of antibiotics found in humans and indicates that the lower ENL concentration may be a consequence of the ecological changes in the microbiota.

  7. Metabolomics to Explore Impact of Dairy Intake

    PubMed Central

    Zheng, Hong; Clausen, Morten R.; Dalsgaard, Trine K.; Bertram, Hanne C.

    2015-01-01

    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. PMID:26091233

  8. Blood transcriptomics and metabolomics for personalized medicine.

    PubMed

    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.

  9. Metabolomics: Definitions and Significance in Systems Biology.

    PubMed

    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.

  10. High-resolution metabolomics of occupational exposure to trichloroethylene.

    PubMed

    Walker, Douglas I; Uppal, Karan; Zhang, Luoping; Vermeulen, Roel; Smith, Martyn; Hu, Wei; Purdue, Mark P; Tang, Xiaojiang; Reiss, Boris; Kim, Sungkyoon; Li, Laiyu; Huang, Hanlin; Pennell, Kurt D; Jones, Dean P; Rothman, Nathaniel; Lan, Qing

    2016-10-01

    Occupational exposure to trichloroethylene (TCE) has been linked to adverse health outcomes including non-Hodgkin's lymphoma and kidney and liver cancer; however, TCE's mode of action for development of these diseases in humans is not well understood. Non-targeted metabolomics analysis of plasma obtained from 80 TCE-exposed workers [full shift exposure range of 0.4 to 230 parts-per-million of air (ppm a )] and 95 matched controls were completed by ultra-high resolution mass spectrometry. Biological response to TCE exposure was determined using a metabolome-wide association study (MWAS) framework, with metabolic changes and plasma TCE metabolites evaluated by dose-response and pathway enrichment. Biological perturbations were then linked to immunological, renal and exposure molecular markers measured in the same population. Metabolic features associated with TCE exposure included known TCE metabolites, unidentifiable chlorinated compounds and endogenous metabolites. Exposure resulted in a systemic response in endogenous metabolism, including disruption in purine catabolism and decreases in sulphur amino acid and bile acid biosynthesis pathways. Metabolite associations with TCE exposure included uric acid (β = 0.13, P-value = 3.6 × 10 -5 ), glutamine (β = 0.08, P-value = 0.0013), cystine (β = 0.75, P-value = 0.0022), methylthioadenosine (β = -1.6, P-value = 0.0043), taurine (β = -2.4, P-value = 0.0011) and chenodeoxycholic acid (β = -1.3, P-value = 0.0039), which are consistent with known toxic effects of TCE, including immunosuppression, hepatotoxicity and nephrotoxicity. Correlation with additional exposure markers and physiological endpoints supported known disease associations. High-resolution metabolomics correlates measured occupational exposure to internal dose and metabolic response, providing insight into molecular mechanisms of exposure-related disease aetiology. © The Author 2016; all rights

  11. Metabolomic Fingerprint of Heart Failure with Preserved Ejection Fraction

    PubMed Central

    Zordoky, Beshay N.; Sung, Miranda M.; Ezekowitz, Justin; Mandal, Rupasri; Han, Beomsoo; Bjorndahl, Trent C.; Bouatra, Souhaila; Anderson, Todd; Oudit, Gavin Y.; Wishart, David S.; Dyck, Jason R. B.

    2015-01-01

    Background Heart failure (HF) with preserved ejection fraction (HFpEF) is increasingly recognized as an important clinical entity. Preclinical studies have shown differences in the pathophysiology between HFpEF and HF with reduced ejection fraction (HFrEF). Therefore, we hypothesized that a systematic metabolomic analysis would reveal a novel metabolomic fingerprint of HFpEF that will help understand its pathophysiology and assist in establishing new biomarkers for its diagnosis. Methods and Results Ambulatory patients with clinical diagnosis of HFpEF (n = 24), HFrEF (n = 20), and age-matched non-HF controls (n = 38) were selected for metabolomic analysis as part of the Alberta HEART (Heart Failure Etiology and Analysis Research Team) project. 181 serum metabolites were quantified by LC-MS/MS and 1H-NMR spectroscopy. Compared to non-HF control, HFpEF patients demonstrated higher serum concentrations of acylcarnitines, carnitine, creatinine, betaine, and amino acids; and lower levels of phosphatidylcholines, lysophosphatidylcholines, and sphingomyelins. Medium and long-chain acylcarnitines and ketone bodies were higher in HFpEF than HFrEF patients. Using logistic regression, two panels of metabolites were identified that can separate HFpEF patients from both non-HF controls and HFrEF patients with area under the receiver operating characteristic (ROC) curves of 0.942 and 0.981, respectively. Conclusions The metabolomics approach employed in this study identified a unique metabolomic fingerprint of HFpEF that is distinct from that of HFrEF. This metabolomic fingerprint has been utilized to identify two novel panels of metabolites that can separate HFpEF patients from both non-HF controls and HFrEF patients. Clinical Trial Registration ClinicalTrials.gov NCT02052804 PMID:26010610

  12. Metabolomics in human type 2 diabetes research.

    PubMed

    Lu, Jingyi; Xie, Guoxiang; Jia, Weiping; Jia, Wei

    2013-03-01

    The high prevalence of diabetes and diabetic complications has caused a huge burden on the modern society. Although scientific advances have led to effective strategies for preventing and treating diabetes over the past several decades, little progress has been made toward curing the disease or even getting it under control, from a public health and overall societal standpoint. There is still a lack of reliable biomarkers indicative of metabolic alterations associated with diabetes and different drug responses, highlighting the need for the development of early diagnostic and prognostic markers for diabetes and diabetic complications. The emergence of metabolomics has allowed researchers to systemically measure the small molecule metabolites, which are sensitive to the changes of both environmental and genetic factors and therefore, could be regarded as the link between genotypes and phenotypes. During the last decade, the progression made in metabolomics has provided insightful information on disease development and disease onset prediction. Recent studies using metabolomics approach coupled with statistical tools to predict incident diabetes revealed a number of metabolites that are significantly altered, including branched-chain and aromatic amino acids, such as isoleucine, leucine, valine, tyrosine and phenylalanine, as diagnostic or highly-significant predictors of future diabetes. This review summarizes the current findings of metabolomic studies in human investigations with the most common form of diabetes, type 2 diabetes.

  13. A strategy for selecting data mining techniques in metabolomics.

    PubMed

    Banimustafa, Ahmed Hmaidan; Hardy, Nigel W

    2012-01-01

    There is a general agreement that the development of metabolomics depends not only on advances in chemical analysis techniques but also on advances in computing and data analysis methods. Metabolomics data usually requires intensive pre-processing, analysis, and mining procedures. Selecting and applying such procedures requires attention to issues including justification, traceability, and reproducibility. We describe a strategy for selecting data mining techniques which takes into consideration the goals of data mining techniques on the one hand, and the goals of metabolomics investigations and the nature of the data on the other. The strategy aims to ensure the validity and soundness of results and promote the achievement of the investigation goals.

  14. Metabolomics for undergraduates: Identification and pathway assignment of mitochondrial metabolites.

    PubMed

    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 approach to identify all the metabolites in a given biological system is called metabolic fingerprinting. Using high-resolution and high-mass accuracy mass spectrometry, large metabolome coverage, sensitivity, and specificity can be attained. Although the theoretical concepts of this methodology are usually provided in life-science programs, hands-on laboratory experiments are not usually accessible to undergraduate students. Even if the instruments are available, there are not simple laboratory protocols created specifically for teaching metabolomics. We designed a straightforward hands-on laboratory experiment to introduce students to this methodology, relating it to biochemical knowledge through metabolic pathway mapping of the identified metabolites. This study focuses on mitochondrial metabolomics since mitochondria have a well-known, medium-sized cellular sub-metabolome. These features facilitate both data processing and pathway mapping. In this experiment, students isolate mitochondria from potatoes, extract the metabolites, and analyze them by high-resolution mass spectrometry (using an FT-ICR mass spectrometer). The resulting mass list is submitted to an online program for metabolite identification, and compounds associated with mitochondrial pathways can be highlighted in a metabolic network map. © 2015 The International Union of Biochemistry and Molecular Biology.

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

    USDA-ARS?s Scientific Manuscript database

    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...

  16. Metabolomic markers of fertility in bull seminal plasma

    PubMed Central

    Dinh, Thu; Kaya, Abdullah; Topper, Einko; Moura, Arlindo Alencar

    2018-01-01

    Metabolites play essential roles in biological systems, but detailed identities and significance of the seminal plasma metabolome related to bull fertility are still unknown. The objectives of this study were to determine the comprehensive metabolome of seminal plasma from Holstein bulls and to ascertain the potential of metabolites as biomarkers of bull fertility. The seminal plasma metabolome from 16 Holstein bulls with two fertility rates were determined by gas chromatography-mass spectrometry (GC-MS). Multivariate and univariate analyses of the data were performed, and the pathways associated with the seminal plasma metabolome were identified using bioinformatics approaches. Sixty-three metabolites were identified in the seminal plasma of all bulls. Fructose was the most abundant metabolite in the seminal fluid, followed for citric acid, lactic acid, urea and phosphoric acid. Androstenedione, 4-ketoglucose, D-xylofuranose, 2-oxoglutaric acid and erythronic acid represented the least predominant metabolites. Partial-Least Squares Discriminant Analysis (PLSDA) revealed a distinct separation between high and low fertility bulls. The metabolites with the greatest Variable Importance in Projection score (VIP > 2) were 2-oxoglutaric acid and fructose. Heat-map analysis, based on VIP score, and univariate analysis indicated that 2-oxoglutaric acid was less (P = 0.02); whereas fructose was greater (P = 0.02) in high fertility than in low fertility bulls. The current study is the first to describe the metabolome of bull seminal plasma using GC-MS and presented metabolites such as 2-oxoglutaric acid and fructose as potential biomarkers of bull fertility. PMID:29634739

  17. Metabolomics: available results, current research projects in breast cancer, and future applications.

    PubMed

    Claudino, Wederson Marcos; Quattrone, Alessandro; Biganzoli, Laura; Pestrin, Marta; Bertini, Ivano; Di Leo, Angelo

    2007-07-01

    Metabolomics is the newest "omics" science. It is a dynamic portrait of the metabolic status of living systems. Metabolomics has brought new insights on metabolic fluxes and a more comprehensive and holistic understanding of a cell's environment. This burgeoning field promises to be a potential tool to fill the gap between genotype and phenotype. As its preceding "omics" sciences (ie, genomics and proteomics), metabolomics' aim is to dredge information hidden in a sea of data. This technology permits simultaneous monitoring of many hundreds, or thousands, of macro- and small molecules, as well as functional monitoring of multiple pivotal cellular pathways. In addition, elucidation of cellular responses to molecular damage, including evolutionarily conserved inducible molecular defense systems, could be achieved with metabolomics and could lead to the discovery of new biomarkers of molecular responses to functional perturbations. If metabolomic information could be translated into diagnostic tests, it might have the potential to impact on clinical practice, and it might lead to the supplementation of traditional biomarkers of cellular integrity, cell and tissue homeostasis, and morphological alterations that result from cell damage or death. In this review the concept and characteristics of metabolomics are introduced. Main current applications of metabolomics in cancer research are reviewed, including its potential in the drug discovery field, and, last but not least, its potential impact in the field of monitoring response and toxicity to anticancer agents. In the last section, research projects ongoing at our institution and future challenges for metabolomics will be presented and briefly discussed.

  18. 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.

    PubMed

    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.

  19. Applications of NMR-based metabolomics in biological and environmental research

    EPA Science Inventory

    As a complimentary tool to other omics platforms, metabolomics is increasingly being used by biologists to study the dynamic response of biological systems (cells, tissues, or whole organisms) under diverse physiological or pathological conditions. Metabolomics deals with the qu...

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

    PubMed

    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 is the comprehensive study of the metabolome, the repertoire of biochemicals (or small molecules) present in cells, tissues, and body fluids. The study of metabolism at the global or "-omics" level is a rapidly growing field that has the potential to have a profound impact upon medical practice. At the center of metabolomics, is the concept that a person's metabolic state provides a close representation of that individual's overall health status. This metabolic state reflects what has been encoded by the genome, and modified by diet, environmental factors, and the gut microbiome. The metabolic profile provides a quantifiable readout of biochemical state from normal physiology to diverse pathophysiologies in a manner that is often not obvious from gene expression analyses. Today, clinicians capture only a very small part of the information contained in the metabolome, as they routinely measure only a narrow set of blood chemistry analytes to assess health and disease states. Examples include measuring glucose to monitor diabetes, measuring cholesterol and high density lipoprotein/low density lipoprotein ratio to assess cardiovascular health, BUN and creatinine for renal disorders, and measuring a panel of metabolites to diagnose potential inborn errors of metabolism in neonates. We anticipate that the narrow range of chemical analyses in current use by the medical community today will be replaced in the future by analyses that reveal a far more comprehensive metabolic signature. This signature is expected to describe global biochemical aberrations that reflect patterns of variance in states of wellness, more accurately describe specific diseases and their progression, and greatly aid in differential diagnosis. Such future metabolic signatures will: (1) provide predictive, prognostic, diagnostic, and surrogate markers of diverse disease states; (2) inform on underlying molecular mechanisms of diseases; (3) allow for sub-classification of diseases, and

  1. [Application of target restoration space quantity and quantitative relation in precise esthetic prosthodontics].

    PubMed

    Haiyang, Yu; Tian, Luo

    2016-06-01

    Target restoration space (TRS) is the most precise space required for designing optimal prosthesis. TRS consists of an internal or external tooth space to confirm the esthetics and function of the final restoration. Therefore, assisted with quantitive analysis transfer, TRS quantitative analysis is a significant improvement for minimum tooth preparation. This article presents TRS quantity-related measurement, analysis, transfer, and internal relevance of three TR. classifications. Results reveal the close bond between precision and minimally invasive treatment. This study can be used to improve the comprehension and execution of precise esthetic prosthodontics.

  2. Development of one novel multiple-target plasmid for duplex quantitative PCR analysis of roundup ready soybean.

    PubMed

    Zhang, Haibo; Yang, Litao; Guo, Jinchao; Li, Xiang; Jiang, Lingxi; Zhang, Dabing

    2008-07-23

    To enforce the labeling regulations of genetically modified organisms (GMOs), the application of reference molecules as calibrators is becoming essential for practical quantification of GMOs. However, the reported reference molecules with tandem marker multiple targets have been proved not suitable for duplex PCR analysis. In this study, we developed one unique plasmid molecule based on one pMD-18T vector with three exogenous target DNA fragments of Roundup Ready soybean GTS 40-3-2 (RRS), that is, CaMV35S, NOS, and RRS event fragments, plus one fragment of soybean endogenous Lectin gene. This Lectin gene fragment was separated from the three exogenous target DNA fragments of RRS by inserting one 2.6 kb DNA fragment with no relatedness to RRS detection targets in this resultant plasmid. Then, we proved that this design allows the quantification of RRS using the three duplex real-time PCR assays targeting CaMV35S, NOS, and RRS events employing this reference molecule as the calibrator. In these duplex PCR assays, the limits of detection (LOD) and quantification (LOQ) were 10 and 50 copies, respectively. For the quantitative analysis of practical RRS samples, the results of accuracy and precision were similar to those of simplex PCR assays, for instance, the quantitative results were at the 1% level, the mean bias of the simplex and duplex PCR were 4.0% and 4.6%, respectively, and the statistic analysis ( t-test) showed that the quantitative data from duplex and simplex PCR had no significant discrepancy for each soybean sample. Obviously, duplex PCR analysis has the advantages of saving the costs of PCR reaction and reducing the experimental errors in simplex PCR testing. The strategy reported in the present study will be helpful for the development of new reference molecules suitable for duplex PCR quantitative assays of GMOs.

  3. Time-resolved comparative metabolomes for Koji fermentation with brown-, white-, and giant embryo-rice.

    PubMed

    Lee, Da Eun; Lee, Sunmin; Singh, Digar; Jang, Eun Seok; Shin, Hye Won; Moon, Byoung Seok; Lee, Choong Hwan

    2017-09-15

    A time-resolved non-targeted metabolomic study towards evaluating the effects of three rice substrate types viz., white rice (WR), giant embryo rice (GER), and brown rice (BR), on Koji fermentation was performed. Notwithstanding the relatively higher proportions of metabolites in unfermented BR (BR 0>WR 0, GER 0), the relative levels of metabolic repertoire in BR Koji were marginally enhanced during 36h fermentation except those for phenolic acids, fatty acids, and vitamins. The WR Koji showed higher levels of lysophospholipids (LysoPC's) and protease-released amino acids (WR 36>GER 36>BR 36). The higher β-glucosidase activity in GER Koji effected the increased levels of sugars and flavonoid aglycons complementing its higher antioxidant activity (GER Koji>BR Koji∼WR Koji). The present study holistically underpins the dynamic metabolomes and enzymatic states during rice Koji fermentation with varying substrate types. The present study finds applications in optimization of commercial Koji production. Copyright © 2017 Elsevier Ltd. All rights reserved.

  4. Metabolomics-Driven Discovery of a Prenylated Isatin Antibiotic Produced by Streptomyces Species MBT28.

    PubMed

    Wu, Changsheng; Du, Chao; Gubbens, Jacob; Choi, Young Hae; van Wezel, Gilles P

    2015-10-23

    Actinomycetes are a major source of antimicrobials, anticancer compounds, and other medically important products, and their genomes harbor extensive biosynthetic potential. Major challenges in the screening of these microorganisms are to activate the expression of cryptic biosynthetic gene clusters and the development of technologies for efficient dereplication of known molecules. Here we report the identification of a previously unidentified isatin-type antibiotic produced by Streptomyces sp. MBT28, following a strategy based on NMR-based metabolomics combined with the introduction of streptomycin resistance in the producer strain. NMR-guided isolation by tracking the target proton signal resulted in the characterization of 7-prenylisatin (1) with antimicrobial activity against Bacillus subtilis. The metabolite-guided genome mining of Streptomyces sp. MBT28 combined with proteomics identified a gene cluster with an indole prenyltransferase that catalyzes the conversion of tryptophan into 7-prenylisatin. This study underlines the applicability of NMR-based metabolomics in facilitating the discovery of novel antibiotics.

  5. Qualitative metabolomics profiling of serum and bile from dogs with gallbladder mucocele formation

    PubMed Central

    Mathews, Kyle G.; Cullen, John; Seiler, Gabriela

    2018-01-01

    Mucocele formation is characterized by secretion of abnormally thick mucus by the gallbladder epithelium of dogs that may cause obstruction of the bile duct or rupture of the gallbladder. The disease is increasingly recognized and is associated with a high morbidity and mortality. The cause of gallbladder mucocele formation in dogs is unknown. There is a strong breed predisposition and affected dogs have a high incidence of concurrent endocrinopathy or hyperlipidemia. These observations suggest a significant influence of both genetic and metabolic factors on disease pathogenesis. In this study, we investigated a theory that mucocele formation is associated with a syndrome of metabolic disruption. We surmised that a global, untargeted metabolomics approach could provide unique insight into the systemic pathogenesis of gallbladder mucocele formation and identify specific compounds as candidate biomarkers or treatment targets. Moreover, concurrent examination of the serum and hepatic duct bile metabolome would enable the construction of mechanism-based theories or identification of specific compounds responsible for altered function of the gallbladder epithelium. Abnormalities observed in dogs with gallbladder mucocele formation, including a 33-fold decrease in serum adenosine 5’-monophosphate (AMP), lower quantities of precursors required for synthesis of energy transporting nucleotides, and increases in citric acid cycle intermediates, suggest excess metabolic energy and a carbon surplus. Altered quantities of compounds involved in protein translation and RNA turnover, together with accumulation of gamma-glutamylated and N-acetylated amino acids in serum suggest abnormal regulation of protein and amino acid metabolism. Increases in lathosterol and 7α-hydroxycholesterol suggest a primary increase in cholesterol synthesis and diversion to bile acid formation. A number of specific biomarker compounds were identified for their ability to distinguish between control

  6. Metabolomic biosignature differentiates melancholic depressive patients from healthy controls.

    PubMed

    Liu, Yashu; Yieh, Lynn; Yang, Tao; Drinkenburg, Wilhelmus; Peeters, Pieter; Steckler, Thomas; Narayan, Vaibhav A; Wittenberg, Gayle; Ye, Jieping

    2016-08-23

    Major depressive disorder (MDD) is a heterogeneous disease at the level of clinical symptoms, and this heterogeneity is likely reflected at the level of biology. Two clinical subtypes within MDD that have garnered interest are "melancholic depression" and "anxious depression". Metabolomics enables us to characterize hundreds of small molecules that comprise the metabolome, and recent work suggests the blood metabolome may be able to inform treatment decisions for MDD, however work is at an early stage. Here we examine a metabolomics data set to (1) test whether clinically homogenous MDD subtypes are also more biologically homogeneous, and hence more predictiable, (2) devise a robust machine learning framework that preserves biological meaning, and (3) describe the metabolomic biosignature for melancholic depression. With the proposed computational system we achieves around 80 % classification accuracy, sensitivity and specificity for melancholic depression, but only ~72 % for anxious depression or MDD, suggesting the blood metabolome contains more information about melancholic depression.. We develop an ensemble feature selection framework (EFSF) in which features are first clustered, and learning then takes place on the cluster centroids, retaining information about correlated features during the feature selection process rather than discarding them as most machine learning methods will do. Analysis of the most discriminative feature clusters revealed differences in metabolic classes such as amino acids and lipids as well as pathways studied extensively in MDD such as the activation of cortisol in chronic stress. We find the greater clinical homogeneity does indeed lead to better prediction based on biological measurements in the case of melancholic depression. Melancholic depression is shown to be associated with changes in amino acids, catecholamines, lipids, stress hormones, and immune-related metabolites. The proposed computational framework can be adapted

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

    PubMed

    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.

  8. Clinical metabolomics paves the way towards future healthcare strategies

    PubMed Central

    Collino, Sebastiano; Martin, François‐Pierre J.; Rezzi, Serge

    2013-01-01

    Metabolomics is recognized as a powerful top‐down system biological approach to understand genetic‐environment‐health paradigms paving new avenues to identify clinically relevant biomarkers. It is nowadays commonly used in clinical applications shedding new light on physiological regulatory processes of complex mammalian systems with regard to disease aetiology, diagnostic stratification and, potentially, mechanism of action of therapeutic solutions. A key feature of metabolomics lies in its ability to underpin the complex metabolic interactions of the host with its commensal microbial partners providing a new way to define individual and population phenotypes. This review aims at describing recent applications of metabolomics in clinical fields with insight into diseases, diagnostics/monitoring and improvement of homeostatic metabolic regulation. PMID:22348240

  9. Metabolomics reveals mycoplasma contamination interferes with the metabolism of PANC-1 cells.

    PubMed

    Yu, Tao; Wang, Yongtao; Zhang, Huizhen; Johnson, Caroline H; Jiang, Yiming; Li, Xiangjun; Wu, Zeming; Liu, Tian; Krausz, Kristopher W; Yu, Aiming; Gonzalez, Frank J; Huang, Min; Bi, Huichang

    2016-06-01

    Mycoplasma contamination is a common problem in cell culture and can alter cellular functions. Since cell metabolism is either directly or indirectly involved in every aspect of cell function, it is important to detect changes to the cellular metabolome after mycoplasma infection. In this study, liquid chromatography mass spectrometry (LC/MS)-based metabolomics was used to investigate the effect of mycoplasma contamination on the cellular metabolism of human pancreatic carcinoma cells (PANC-1). Multivariate analysis demonstrated that mycoplasma contamination induced significant metabolic changes in PANC-1 cells. Twenty-three metabolites were identified and found to be involved in arginine and purine metabolism and energy supply. This study demonstrates that mycoplasma contamination significantly alters cellular metabolite levels, confirming the compelling need for routine checking of cell cultures for mycoplasma contamination, particularly when used for metabolomics studies. Graphical abstract Metabolomics reveals mycoplasma contamination changes the metabolome of PANC-1 cells.

  10. Large-scale neurochemical metabolomics analysis identifies multiple compounds associated with methamphetamine exposure.

    PubMed

    McClay, Joseph L; Adkins, Daniel E; Vunck, Sarah A; Batman, Angela M; Vann, Robert E; Clark, Shaunna L; Beardsley, Patrick M; van den Oord, Edwin J C G

    2013-04-01

    Methamphetamine (MA) is an illegal stimulant drug of abuse with serious negative health consequences. The neurochemical effects of MA have been partially characterized, with a traditional focus on classical neurotransmitter systems. However, these directions have not yet led to novel drug treatments for MA abuse or toxicity. As an alternative approach, we describe here the first application of metabolomics to investigate the neurochemical consequences of MA exposure in the rodent brain. We examined single exposures at 3 mg/kg and repeated exposures at 3 mg/kg over 5 days in eight common inbred mouse strains. Brain tissue samples were assayed using high-throughput gas and liquid chromatography mass spectrometry, yielding quantitative data on >300 unique metabolites. Association testing and false discovery rate control yielded several metabolome-wide significant associations with acute MA exposure, including compounds such as lactate ( p = 4.4 × 10 -5 , q = 0.013), tryptophan ( p = 7.0 × 10 -4 , q = 0.035) and 2-hydroxyglutarate ( p = 1.1 × 10 -4 , q = 0.022). Secondary analyses of MA-induced increase in locomotor activity showed associations with energy metabolites such as succinate ( p = 3.8 × 10 -7 ). Associations specific to repeated (5 day) MA exposure included phosphocholine ( p = 4.0 × 10 -4 , q = 0.087) and ergothioneine ( p = 3.0 × 10 -4 , q = 0.087). Our data appear to confirm and extend existing models of MA action in the brain, whereby an initial increase in energy metabolism, coupled with an increase in behavioral locomotion, gives way to disruption of mitochondria and phospholipid pathways and increased endogenous antioxidant response. Our study demonstrates the power of comprehensive MS-based metabolomics to identify drug-induced changes to brain metabolism and to develop neurochemical models of drug effects.

  11. Large-scale neurochemical metabolomics analysis identifies multiple compounds associated with methamphetamine exposure

    PubMed Central

    Adkins, Daniel E.; Vunck, Sarah A.; Batman, Angela M.; Vann, Robert E.; Clark, Shaunna L.; Beardsley, Patrick M.; van den Oord, Edwin J. C. G.

    2012-01-01

    Methamphetamine (MA) is an illegal stimulant drug of abuse with serious negative health consequences. The neurochemical effects of MA have been partially characterized, with a traditional focus on classical neurotransmitter systems. However, these directions have not yet led to novel drug treatments for MA abuse or toxicity. As an alternative approach, we describe here the first application of metabolomics to investigate the neurochemical consequences of MA exposure in the rodent brain. We examined single exposures at 3 mg/kg and repeated exposures at 3 mg/kg over 5 days in eight common inbred mouse strains. Brain tissue samples were assayed using high-throughput gas and liquid chromatography mass spectrometry, yielding quantitative data on >300 unique metabolites. Association testing and false discovery rate control yielded several metabolome-wide significant associations with acute MA exposure, including compounds such as lactate (p = 4.4 × 10−5, q = 0.013), tryptophan (p = 7.0 × 10−4, q = 0.035) and 2-hydroxyglutarate (p = 1.1 × 10−4, q = 0.022). Secondary analyses of MA-induced increase in locomotor activity showed associations with energy metabolites such as succinate (p = 3.8 × 10−7). Associations specific to repeated (5 day) MA exposure included phosphocholine (p = 4.0 × 10−4, q = 0.087) and ergothioneine (p = 3.0 × 10−4, q = 0.087). Our data appear to confirm and extend existing models of MA action in the brain, whereby an initial increase in energy metabolism, coupled with an increase in behavioral locomotion, gives way to disruption of mitochondria and phospholipid pathways and increased endogenous antioxidant response. Our study demonstrates the power of comprehensive MS-based metabolomics to identify drug-induced changes to brain metabolism and to develop neurochemical models of drug effects. PMID:23554582

  12. Impact of Anesthesia and Euthanasia on Metabolomics of Mammalian Tissues: Studies in a C57BL/6J Mouse Model

    PubMed Central

    Overmyer, Katherine A.; Thonusin, Chanisa; Qi, Nathan R.; Burant, Charles F.; Evans, Charles R.

    2015-01-01

    A critical application of metabolomics is the evaluation of tissues, which are often the primary sites of metabolic dysregulation in disease. Laboratory rodents have been widely used for metabolomics studies involving tissues due to their facile handing, genetic manipulability and similarity to most aspects of human metabolism. However, the necessary step of administration of anesthesia in preparation for tissue sampling is not often given careful consideration, in spite of its potential for causing alterations in the metabolome. We examined, for the first time using untargeted and targeted metabolomics, the effect of several commonly used methods of anesthesia and euthanasia for collection of skeletal muscle, liver, heart, adipose and serum of C57BL/6J mice. The data revealed dramatic, tissue-specific impacts of tissue collection strategy. Among many differences observed, post-euthanasia samples showed elevated levels of glucose 6-phosphate and other glycolytic intermediates in skeletal muscle. In heart and liver, multiple nucleotide and purine degradation metabolites accumulated in tissues of euthanized compared to anesthetized animals. Adipose tissue was comparatively less affected by collection strategy, although accumulation of lactate and succinate in euthanized animals was observed in all tissues. Among methods of tissue collection performed pre-euthanasia, ketamine showed more variability compared to isoflurane and pentobarbital. Isoflurane induced elevated liver aspartate but allowed more rapid initiation of tissue collection. Based on these findings, we present a more optimal collection strategy mammalian tissues and recommend that rodent tissues intended for metabolomics studies be collected under anesthesia rather than post-euthanasia. PMID:25658945

  13. Impact of anesthesia and euthanasia on metabolomics of mammalian tissues: studies in a C57BL/6J mouse model.

    PubMed

    Overmyer, Katherine A; Thonusin, Chanisa; Qi, Nathan R; Burant, Charles F; Evans, Charles R

    2015-01-01

    A critical application of metabolomics is the evaluation of tissues, which are often the primary sites of metabolic dysregulation in disease. Laboratory rodents have been widely used for metabolomics studies involving tissues due to their facile handing, genetic manipulability and similarity to most aspects of human metabolism. However, the necessary step of administration of anesthesia in preparation for tissue sampling is not often given careful consideration, in spite of its potential for causing alterations in the metabolome. We examined, for the first time using untargeted and targeted metabolomics, the effect of several commonly used methods of anesthesia and euthanasia for collection of skeletal muscle, liver, heart, adipose and serum of C57BL/6J mice. The data revealed dramatic, tissue-specific impacts of tissue collection strategy. Among many differences observed, post-euthanasia samples showed elevated levels of glucose 6-phosphate and other glycolytic intermediates in skeletal muscle. In heart and liver, multiple nucleotide and purine degradation metabolites accumulated in tissues of euthanized compared to anesthetized animals. Adipose tissue was comparatively less affected by collection strategy, although accumulation of lactate and succinate in euthanized animals was observed in all tissues. Among methods of tissue collection performed pre-euthanasia, ketamine showed more variability compared to isoflurane and pentobarbital. Isoflurane induced elevated liver aspartate but allowed more rapid initiation of tissue collection. Based on these findings, we present a more optimal collection strategy mammalian tissues and recommend that rodent tissues intended for metabolomics studies be collected under anesthesia rather than post-euthanasia.

  14. Non-targeted plasma metabolomic profile at early and late lactation in parity 1 dams with diverging body composition at weaning

    USDA-ARS?s Scientific Manuscript database

    Lactation is an extremely energy demanding event, impacting naïve dams to a greater extent as they are still physiologically immature. The objective of the current study was to determine if a unique plasma metabolome exists at early and late lactation from first parity gilts having similar body meas...

  15. Time-resolved metabolomics reveals metabolic modulation in rice foliage

    PubMed Central

    Sato, Shigeru; Arita, Masanori; Soga, Tomoyoshi; Nishioka, Takaaki; Tomita, Masaru

    2008-01-01

    Background To elucidate the interaction of dynamics among modules that constitute biological systems, comprehensive datasets obtained from "omics" technologies have been used. In recent plant metabolomics approaches, the reconstruction of metabolic correlation networks has been attempted using statistical techniques. However, the results were unsatisfactory and effective data-mining techniques that apply appropriate comprehensive datasets are needed. Results Using capillary electrophoresis mass spectrometry (CE-MS) and capillary electrophoresis diode-array detection (CE-DAD), we analyzed the dynamic changes in the level of 56 basic metabolites in plant foliage (Oryza sativa L. ssp. japonica) at hourly intervals over a 24-hr period. Unsupervised clustering of comprehensive metabolic profiles using Kohonen's self-organizing map (SOM) allowed classification of the biochemical pathways activated by the light and dark cycle. The carbon and nitrogen (C/N) metabolism in both periods was also visualized as a phenotypic linkage map that connects network modules on the basis of traditional metabolic pathways rather than pairwise correlations among metabolites. The regulatory networks of C/N assimilation/dissimilation at each time point were consistent with previous works on plant metabolism. In response to environmental stress, glutathione and spermidine fluctuated synchronously with their regulatory targets. Adenine nucleosides and nicotinamide coenzymes were regulated by phosphorylation and dephosphorylation. We also demonstrated that SOM analysis was applicable to the estimation of unidentifiable metabolites in metabolome analysis. Hierarchical clustering of a correlation coefficient matrix could help identify the bottleneck enzymes that regulate metabolic networks. Conclusion Our results showed that our SOM analysis with appropriate metabolic time-courses effectively revealed the synchronous dynamics among metabolic modules and elucidated the underlying biochemical

  16. Optimizing Nanoscale Quantitative Optical Imaging of Subfield Scattering Targets

    PubMed Central

    Henn, Mark-Alexander; Barnes, Bryan M.; Zhou, Hui; Sohn, Martin; Silver, Richard M.

    2016-01-01

    The full 3-D scattered field above finite sets of features has been shown to contain a continuum of spatial frequency information, and with novel optical microscopy techniques and electromagnetic modeling, deep-subwavelength geometrical parameters can be determined. Similarly, by using simulations, scattering geometries and experimental conditions can be established to tailor scattered fields that yield lower parametric uncertainties while decreasing the number of measurements and the area of such finite sets of features. Such optimized conditions are reported through quantitative optical imaging in 193 nm scatterfield microscopy using feature sets up to four times smaller in area than state-of-the-art critical dimension targets. PMID:27805660

  17. Spectral relative standard deviation: a practical benchmark in metabolomics.

    PubMed

    Parsons, Helen M; Ekman, Drew R; Collette, Timothy W; Viant, Mark R

    2009-03-01

    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 assess the reproducibility of metabolomics datasets that are derived from all the detected metabolites. Here we calculate spectrum-wide relative standard deviations (RSDs; also termed coefficient of variation, CV) for ten metabolomics datasets, spanning a variety of sample types from mammals, fish, invertebrates and a cell line, and display them succinctly as boxplots. We demonstrate multiple applications of spectral RSDs for characterising technical as well as inter-individual biological variation: for optimising metabolite extractions, comparing analytical techniques, investigating matrix effects, and comparing biofluids and tissue extracts from single and multiple species for optimising experimental design. Technical variation within metabolomics datasets, recorded using one- and two-dimensional NMR and mass spectrometry, ranges from 1.6 to 20.6% (reported as the median spectral RSD). Inter-individual biological variation is typically larger, ranging from as low as 7.2% for tissue extracts from laboratory-housed rats to 58.4% for fish plasma. In addition, for some of the datasets we confirm that the spectral RSD values are largely invariant across different spectral processing methods, such as baseline correction, normalisation and binning resolution. In conclusion, we propose spectral RSDs and their median values contained herein as practical benchmarks for metabolomics studies.

  18. Metabolomics and Metabolic Diseases: Where Do We Stand?

    PubMed

    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. Improved Quantitative Plant Proteomics via the Combination of Targeted and Untargeted Data Acquisition

    PubMed Central

    Hart-Smith, Gene; Reis, Rodrigo S.; Waterhouse, Peter M.; Wilkins, Marc R.

    2017-01-01

    Quantitative proteomics strategies – which are playing important roles in the expanding field of plant molecular systems biology – are traditionally designated as either hypothesis driven or non-hypothesis driven. Many of these strategies aim to select individual peptide ions for tandem mass spectrometry (MS/MS), and to do this mixed hypothesis driven and non-hypothesis driven approaches are theoretically simple to implement. In-depth investigations into the efficacies of such approaches have, however, yet to be described. In this study, using combined samples of unlabeled and metabolically 15N-labeled Arabidopsis thaliana proteins, we investigate the mixed use of targeted data acquisition (TDA) and data dependent acquisition (DDA) – referred to as TDA/DDA – to facilitate both hypothesis driven and non-hypothesis driven quantitative data collection in individual LC-MS/MS experiments. To investigate TDA/DDA for hypothesis driven data collection, 7 miRNA target proteins of differing size and abundance were targeted using inclusion lists comprised of 1558 m/z values, using 3 different TDA/DDA experimental designs. In samples in which targeted peptide ions were of particularly low abundance (i.e., predominantly only marginally above mass analyser detection limits), TDA/DDA produced statistically significant increases in the number of targeted peptides identified (230 ± 8 versus 80 ± 3 for DDA; p = 1.1 × 10-3) and quantified (35 ± 3 versus 21 ± 2 for DDA; p = 0.038) per experiment relative to the use of DDA only. These expected improvements in hypothesis driven data collection were observed alongside unexpected improvements in non-hypothesis driven data collection. Untargeted peptide ions with m/z values matching those in inclusion lists were repeatedly identified and quantified across technical replicate TDA/DDA experiments, resulting in significant increases in the percentages of proteins repeatedly quantified in TDA/DDA experiments only relative to DDA

  20. Metabolomics: a state-of-the-art technology for better understanding of male infertility.

    PubMed

    Minai-Tehrani, A; Jafarzadeh, N; Gilany, K

    2016-08-01

    Male factor infertility affects approximately half of the infertile couples, in spite of many years of research on male infertility treatment and diagnosis; several outstanding questions remain to be addressed. In this regard, metabolomics as a novel field of omics has been suggested to be applied for male infertility problems. A variety of terms associated with metabolite quantity and quality have been established to demonstrate mixtures of metabolites. Despite metabolomics and metabolite analyses have been around more than decades, a limited number of studies concerning male infertility have been carried out. In this review, we summarised the latest finding in metabolomics techniques and metabolomics biomarkers correlated with male infertility. The rapid progress of a variety of metabolomics platforms, such as nonoptical and optical spectroscopy, could ease separation, recognition, classification and quantification of several metabolites and their metabolic pathways. Here, we recommend that the novel biomarkers determined in the course of metabolomics analysis may stand for potential application of treatment and future clinical practice. © 2015 Blackwell Verlag GmbH.

  1. Metabolomics method to comprehensively analyze amino acids in different domains.

    PubMed

    Gu, Haiwei; Du, Jianhai; Carnevale Neto, Fausto; Carroll, Patrick A; Turner, Sally J; Chiorean, E Gabriela; Eisenman, Robert N; Raftery, Daniel

    2015-04-21

    Amino acids play essential roles in both metabolism and the proteome. Many studies have profiled free amino acids (FAAs) or proteins; however, few have connected the measurement of FAA with individual amino acids in the proteome. In this study, we developed a metabolomics method to comprehensively analyze amino acids in different domains, using two examples of different sample types and disease models. We first examined the responses of FAAs and insoluble-proteome amino acids (IPAAs) to the Myc oncogene in Tet21N human neuroblastoma cells. The metabolic and proteomic amino acid profiles were quite different, even under the same Myc condition, and their combination provided a better understanding of the biological status. In addition, amino acids were measured in 3 domains (FAAs, free and soluble-proteome amino acids (FSPAAs), and IPAAs) to study changes in serum amino acid profiles related to colon cancer. A penalized logistic regression model based on the amino acids from the three domains had better sensitivity and specificity than that from each individual domain. To the best of our knowledge, this is the first study to perform a combined analysis of amino acids in different domains, and indicates the useful biological information available from a metabolomics analysis of the protein pellet. This study lays the foundation for further quantitative tracking of the distribution of amino acids in different domains, with opportunities for better diagnosis and mechanistic studies of various diseases.

  2. PepsNMR for 1H NMR metabolomic data pre-processing.

    PubMed

    Martin, Manon; Legat, Benoît; Leenders, Justine; Vanwinsberghe, Julien; Rousseau, Réjane; Boulanger, Bruno; Eilers, Paul H C; De Tullio, Pascal; Govaerts, Bernadette

    2018-08-17

    In the analysis of biological samples, control over experimental design and data acquisition procedures alone cannot ensure well-conditioned 1 H NMR spectra with maximal information recovery for data analysis. A third major element affects the accuracy and robustness of results: the data pre-processing/pre-treatment for which not enough attention is usually devoted, in particular in metabolomic studies. The usual approach is to use proprietary software provided by the analytical instruments' manufacturers to conduct the entire pre-processing strategy. This widespread practice has a number of advantages such as a user-friendly interface with graphical facilities, but it involves non-negligible drawbacks: a lack of methodological information and automation, a dependency of subjective human choices, only standard processing possibilities and an absence of objective quality criteria to evaluate pre-processing quality. This paper introduces PepsNMR to meet these needs, an R package dedicated to the whole processing chain prior to multivariate data analysis, including, among other tools, solvent signal suppression, internal calibration, phase, baseline and misalignment corrections, bucketing and normalisation. Methodological aspects are discussed and the package is compared to the gold standard procedure with two metabolomic case studies. The use of PepsNMR on these data shows better information recovery and predictive power based on objective and quantitative quality criteria. Other key assets of the package are workflow processing speed, reproducibility, reporting and flexibility, graphical outputs and documented routines. Copyright © 2018 Elsevier B.V. All rights reserved.

  3. Metabolomic Responses of Arabidopsis Suspension Cells to Bicarbonate under Light and Dark Conditions

    PubMed Central

    Misra, Biswapriya B.; Yin, Zepeng; Geng, Sisi; de Armas, Evaldo; Chen, Sixue

    2016-01-01

    Global CO2 level presently recorded at 400 ppm is expected to reach 550 ppm in 2050, an increment likely to impact plant growth and productivity. Using targeted LC-MS and GC-MS platforms we quantified 229 and 29 metabolites, respectively in a time-course study to reveal short-term responses to different concentrations (1, 3, and 10 mM) of bicarbonate (HCO3−) under light and dark conditions. Results indicate that HCO3− treatment responsive metabolomic changes depend on the HCO3− concentration, time of treatment, and light/dark. Interestingly, 3 mM HCO3− concentration treatment induced more significantly changed metabolites than either lower or higher concentrations used. Flavonoid biosynthesis and glutathione metabolism were common to both light and dark-mediated responses in addition to showing concentration-dependent changes. Our metabolomics results provide insights into short-term plant cellular responses to elevated HCO3− concentrations as a result of ambient increases in CO2 under light and dark. PMID:27762345

  4. Enabling Quantitative Optical Imaging for In-die-capable Critical Dimension Targets

    PubMed Central

    Barnes, B.M.; Henn, M.-A.; Sohn, M. Y.; Zhou, H.; Silver, R. M.

    2017-01-01

    Dimensional scaling trends will eventually bring semiconductor critical dimensions (CDs) down to only a few atoms in width. New optical techniques are required to address the measurement and variability for these CDs using sufficiently small in-die metrology targets. Recently, Qin et al. [Light Sci Appl, 5, e16038 (2016)] demonstrated quantitative model-based measurements of finite sets of lines with features as small as 16 nm using 450 nm wavelength light. This paper uses simulation studies, augmented with experiments at 193 nm wavelength, to adapt and optimize the finite sets of features that work as in-die-capable metrology targets with minimal increases in parametric uncertainty. A finite element based solver for time-harmonic Maxwell's equations yields two- and three-dimensional simulations of the electromagnetic scattering for optimizing the design of such targets as functions of reduced line lengths, fewer number of lines, fewer focal positions, smaller critical dimensions, and shorter illumination wavelength. Metrology targets that exceeded performance requirements are as short as 3 μm for 193 nm light, feature as few as eight lines, and are extensible to sub-10 nm CDs. Target areas measured at 193 nm can be fifteen times smaller in area than current state-of-the-art scatterometry targets described in the literature. This new methodology is demonstrated to be a promising alternative for optical model-based in-die CD metrology. PMID:28757674

  5. Biological effect of aqueous C60 aggregates on Scenedesmus obliquus revealed by transcriptomics and non-targeted metabolomics.

    PubMed

    Du, Chunlei; Zhang, Bo; He, Yiliang; Hu, Chaoyang; Ng, Qin Xiang; Zhang, Hui; Ong, Choon Nam; ZhifenLin

    2017-02-15

    This work evaluated biological effect of nC 60 on Scenedesmus obliquus. The cells were exposed to various concentrations of nC 60 for 7days. Low-dose of nC 60 was found to have a minor growth inhibitory effect. The transcriptomics and metabolomics were integrated to examine intricate molecular and cellular effects of nC 60 on Scenedesmus obliquus. We found that Scenedesmus obliquus cells exposed to nC 60 had several significant alterations in cellular transcription and biochemical processes. During the 7-day exposure to nC 60 , 2234 and 2,448 unigenes were differentially expressed by 0.1mg/L and 1mg/L nC 60 -treated groups compared with the control, including 2085 or 2247 up-regulated genes and 149 or 201 down-regulated genes, respectively. We successfully identified 22 metabolites, including 6 significantly changed metabolites, such as sucrose, d-glucose, and malic acid. The citrate cycle (TCA cycle) (ko00020) was the main target of both differentially expressed genes and metabolic change. However, accumulation of sucrose (end-product) could have induced feedback inhibition of photosynthesis in Scenedesmus obliquus, explaining the slight growth inhibition observed. The results provided a mechanistic understanding of the growth inhibition of nC 60 toxicity. These genes and metabolites are useful biomarkers for future studies and offer new insights into the early detectable changes in Scenedesmus obliquus with nC 60 exposure. Copyright © 2016 Elsevier B.V. All rights reserved.

  6. Metabolomics for Undergraduates: Identification and Pathway Assignment of Mitochondrial Metabolites

    ERIC Educational Resources Information Center

    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…

  7. Quantitative ultrasound molecular imaging by modeling the binding kinetics of targeted contrast agent

    NASA Astrophysics Data System (ADS)

    Turco, Simona; Tardy, Isabelle; Frinking, Peter; Wijkstra, Hessel; Mischi, Massimo

    2017-03-01

    Ultrasound molecular imaging (USMI) is an emerging technique to monitor diseases at the molecular level by the use of novel targeted ultrasound contrast agents (tUCA). These consist of microbubbles functionalized with targeting ligands with high-affinity for molecular markers of specific disease processes, such as cancer-related angiogenesis. Among the molecular markers of angiogenesis, the vascular endothelial growth factor receptor 2 (VEGFR2) is recognized to play a major role. In response, the clinical-grade tUCA BR55 was recently developed, consisting of VEGFR2-targeting microbubbles which can flow through the entire circulation and accumulate where VEGFR2 is over-expressed, thus causing selective enhancement in areas of active angiogenesis. Discrimination between bound and free microbubbles is crucial to assess cancer angiogenesis. Currently, this is done non-quantitatively by looking at the late enhancement, about 10 min after injection, or by calculation of the differential targeted enhancement, requiring the application of a high-pressure ultrasound (US) burst to destroy all the microbubbles in the acoustic field and isolate the signal coming only from bound microbubbles. In this work, we propose a novel method based on mathematical modeling of the binding kinetics during the tUCA first pass, thus reducing the acquisition time and with no need for a destructive US burst. Fitting time-intensity curves measured with USMI by the proposed model enables the assessment of cancer angiogenesis at both the vascular and molecular levels. This is achieved by estimation of quantitative parameters related to the microvascular architecture and microbubble binding. The proposed method was tested in 11 prostate-tumor bearing rats by performing USMI after injection of BR55, and showed good agreement with current USMI methods. The novel information provided by the proposed method, possibly combined with the current non-quantitative methods, may bring deeper insight into

  8. Metabolomics in Toxicology and Preclinical Research, a t4 Workshop Report

    EPA Science Inventory

    Metabolomics, the comprehensive analysis of metabolites in a biological system, provides detailed information about the biochemical/physiological condition of the test system, and of changes affected by anthropogenic chemicals. Metabolomic analysis is used in many fields, ranging...

  9. Standard Reporting Requirements for Biological Samples in Metabolomics Experiments: Environmental Context

    EPA Science Inventory

    Metabolomic technologies are increasingly being applied to study biological questions in a range of different settings from clinical through to environmental. As with other high-throughput technologies, such as those used in transcriptomics and proteomics, metabolomics continues...

  10. Recommendations and Standardization of Biomarker Quantification Using NMR-Based Metabolomics with Particular Focus on Urinary Analysis.

    PubMed

    Emwas, Abdul-Hamid; Roy, Raja; McKay, Ryan T; Ryan, Danielle; Brennan, Lorraine; Tenori, Leonardo; Luchinat, Claudio; Gao, Xin; Zeri, Ana Carolina; Gowda, G A Nagana; Raftery, Daniel; Steinbeck, Christoph; Salek, Reza M; Wishart, David S

    2016-02-05

    NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to nondestructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Precise metabolite quantification is a prerequisite to move any chemical biomarker or biomarker panel from the lab to the clinic. Among the biofluids commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, and easily obtained, needs little sample preparation, and does not require invasive medical procedures for collection. Furthermore, urine captures and concentrates many "unwanted" or "undesirable" compounds throughout the body, providing a rich source of potentially useful disease biomarkers; however, incredible variation in urine chemical concentrations makes analysis of urine and identification of useful urinary biomarkers by NMR challenging. We discuss a number of the most significant issues regarding NMR-based urinary metabolomics with specific emphasis on metabolite quantification for disease biomarker applications and propose data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, sample preparation, and biomarker assessment.

  11. Simultaneous measurement of NAD metabolome in aged mice tissue using liquid chromatography tandem-mass spectrometry.

    PubMed

    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.

  12. Metabolomics discloses donor liver biomarkers associated with early allograft dysfunction.

    PubMed

    Cortes, Miriam; Pareja, Eugenia; García-Cañaveras, Juan C; Donato, M Teresa; Montero, Sandra; Mir, Jose; Castell, José V; Lahoz, Agustín

    2014-09-01

    Early allograft dysfunction (EAD) dramatically influences graft and patient outcome after orthotopic liver transplantation and its incidence is strongly determined by donor liver quality. Nevertheless, objective biomarkers, which can assess graft quality and anticipate organ function, are still lacking. This study aims to investigate whether there is a preoperative donor liver metabolomic biosignature associated with EAD. A comprehensive metabolomic profiling of 124 donor liver biopsies collected before transplantation was performed by mass spectrometry coupled to liquid chromatography. Donor liver grafts were classified into two groups: showing EAD and immediate graft function (IGF). Multivariate data analysis was used to search for the relationship between the metabolomic profiles present in donor livers before transplantation and their function in recipients. A set of liver graft dysfunction-associated biomarkers was identified. Key changes include significantly increased levels of bile acids, lysophospholipids, phospholipids, sphingomyelins and histidine metabolism products, all suggestive of disrupted lipid homeostasis and altered histidine pathway. Based on these biomarkers, a predictive EAD model was built and further evaluated by assessing 24 independent donor livers, yielding 91% sensitivity and 82% specificity. The model was also successfully challenged by evaluating donor livers showing primary non-function (n=4). A metabolomic biosignature that accurately differentiates donor livers, which later showed EAD or IGF, has been deciphered. The remarkable metabolomic differences between donor livers before transplant can relate to their different quality. The proposed metabolomic approach may become a clinical tool for donor liver quality assessment and for anticipating graft function before transplant. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

  13. Metabolomics in Population-Based Research

    Cancer.gov

    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.

  14. The Importance of Experimental Design, Quality Assurance, and Control in Plant Metabolomics Experiments.

    PubMed

    Martins, Marina C M; Caldana, Camila; Wolf, Lucia Daniela; de Abreu, Luis Guilherme Furlan

    2018-01-01

    The output of metabolomics relies to a great extent upon the methods and instrumentation to identify, quantify, and access spatial information on as many metabolites as possible. However, the most modern machines and sophisticated tools for data analysis cannot compensate for inappropriate harvesting and/or sample preparation procedures that modify metabolic composition and can lead to erroneous interpretation of results. In addition, plant metabolism has a remarkable degree of complexity, and the number of identified compounds easily surpasses the number of samples in metabolomics analyses, increasing false discovery risk. These aspects pose a large challenge when carrying out plant metabolomics experiments. In this chapter, we address the importance of a proper experimental design taking into consideration preventable complications and unavoidable factors to achieve success in metabolomics analysis. We also focus on quality control and standardized procedures during the metabolomics workflow.

  15. Strategies Involving Mass Spectrometry Combined with Capillary Electrophoresis in Metabolomics.

    PubMed

    Rodrigues, Karina Trevisan; Cieslarová, Zuzana; Tavares, Marina Franco Maggi; Simionato, Ana Valéria Colnaghi

    2017-01-01

    This chapter focuses on the important contribution of CE-MS in metabolomics, describing the nature of CE-MS coupling and the technical improvements that have led to the interfaces used in modern instrumentation. Moreover, it will discourse how the variety of electrolyte compositions and additives, which has conferred CE the exceptional selectivity of its multiple separation modes, has been handled to allow interfacing with MS without compromising ionization efficiency and the spectrometer integrity. Finally, the methodologies of CE-MS in current use for metabolomics will be discussed in detail. To verify the scope of CE-MS in clinical metabolomics, a myriad of representative applications has been compiled.

  16. Metabolomic Technologies for Improving the Quality of Food: Practice and Promise.

    PubMed

    Johanningsmeier, Suzanne D; Harris, G Keith; Klevorn, Claire M

    2016-01-01

    It is now well documented that the diet has a significant impact on human health and well-being. However, the complete set of small molecule metabolites present in foods that make up the human diet and the role of food production systems in altering this food metabolome are still largely unknown. Metabolomic platforms that rely on nuclear magnetic resonance (NMR) and mass spectrometry (MS) analytical technologies are being employed to study the impact of agricultural practices, processing, and storage on the global chemical composition of food; to identify novel bioactive compounds; and for authentication and region-of-origin classifications. This review provides an overview of the current terminology, analytical methods, and compounds associated with metabolomic studies, and provides insight into the application of metabolomics to generate new knowledge that enables us to produce, preserve, and distribute high-quality foods for health promotion.

  17. Growth of Malignant Non-CNS Tumors Alters Brain Metabolome

    PubMed Central

    Kovalchuk, Anna; Nersisyan, Lilit; Mandal, Rupasri; Wishart, David; Mancini, Maria; Sidransky, David; Kolb, Bryan; Kovalchuk, Olga

    2018-01-01

    Cancer survivors experience numerous treatment side effects that negatively affect their quality of life. Cognitive side effects are especially insidious, as they affect memory, cognition, and learning. Neurocognitive deficits occur prior to cancer treatment, arising even before cancer diagnosis, and we refer to them as “tumor brain.” Metabolomics is a new area of research that focuses on metabolome profiles and provides important mechanistic insights into various human diseases, including cancer, neurodegenerative diseases, and aging. Many neurological diseases and conditions affect metabolic processes in the brain. However, the tumor brain metabolome has never been analyzed. In our study we used direct flow injection/mass spectrometry (DI-MS) analysis to establish the effects of the growth of lung cancer, pancreatic cancer, and sarcoma on the brain metabolome of TumorGraft™ mice. We found that the growth of malignant non-CNS tumors impacted metabolic processes in the brain, affecting protein biosynthesis, and amino acid and sphingolipid metabolism. The observed metabolic changes were similar to those reported for neurodegenerative diseases and brain aging, and may have potential mechanistic value for future analysis of the tumor brain phenomenon. PMID:29515623

  18. Deep Learning Accurately Predicts Estrogen Receptor Status in Breast Cancer Metabolomics Data.

    PubMed

    Alakwaa, Fadhl M; Chaudhary, Kumardeep; Garmire, Lana X

    2018-01-05

    Metabolomics holds the promise as a new technology to diagnose highly heterogeneous diseases. Conventionally, metabolomics data analysis for diagnosis is done using various statistical and machine learning based classification methods. However, it remains unknown if deep neural network, a class of increasingly popular machine learning methods, is suitable to classify metabolomics data. Here we use a cohort of 271 breast cancer tissues, 204 positive estrogen receptor (ER+), and 67 negative estrogen receptor (ER-) to test the accuracies of feed-forward networks, a deep learning (DL) framework, as well as six widely used machine learning models, namely random forest (RF), support vector machines (SVM), recursive partitioning and regression trees (RPART), linear discriminant analysis (LDA), prediction analysis for microarrays (PAM), and generalized boosted models (GBM). DL framework has the highest area under the curve (AUC) of 0.93 in classifying ER+/ER- patients, compared to the other six machine learning algorithms. Furthermore, the biological interpretation of the first hidden layer reveals eight commonly enriched significant metabolomics pathways (adjusted P-value <0.05) that cannot be discovered by other machine learning methods. Among them, protein digestion and absorption and ATP-binding cassette (ABC) transporters pathways are also confirmed in integrated analysis between metabolomics and gene expression data in these samples. In summary, deep learning method shows advantages for metabolomics based breast cancer ER status classification, with both the highest prediction accuracy (AUC = 0.93) and better revelation of disease biology. We encourage the adoption of feed-forward networks based deep learning method in the metabolomics research community for classification.

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

    PubMed

    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.

  20. A Multiplatform Metabolomic Approach to the Basis of Antimonial Action and Resistance in Leishmania infantum

    PubMed Central

    Castilho-Martins, Emerson A.; Tavares, Marina F. M.; Barbas, Coral; López-Gonzálvez, Ángeles; Rivas, Luis

    2015-01-01

    There is a rising resistance against antimony drugs, the gold-standard for treatment until some years ago. That is a serious problem due to the paucity of drugs in current clinical use. In a research to reveal how these drugs affect the parasite during treatment and to unravel the underlying basis for their resistance, we have employed metabolomics to study treatment in Leishmania infantum promastigotes. This was accomplished first through the untargeted analysis of metabolic snapshots of treated and untreated parasites both resistant and responders, utilizing a multiplatform approach to give the widest as possible coverage of the metabolome, and additionally through novel monitoring of the origin of the detected alterations through a 13C traceability experiment. Our data stress a multi-target metabolic alteration with treatment, affecting in particular the cell redox system that is essential to cope with detoxification and biosynthetic processes. Additionally, relevant changes were noted in amino acid metabolism. Our results are in agreement with other authors studying other Leishmania species. PMID:26161866

  1. xMSanalyzer: automated pipeline for improved feature detection and downstream analysis of large-scale, non-targeted metabolomics data.

    PubMed

    Uppal, Karan; Soltow, Quinlyn A; Strobel, Frederick H; Pittard, W Stephen; Gernert, Kim M; Yu, Tianwei; Jones, Dean P

    2013-01-16

    Detection of low abundance metabolites is important for de novo mapping of metabolic pathways related to diet, microbiome or environmental exposures. Multiple algorithms are available to extract m/z features from liquid chromatography-mass spectral data in a conservative manner, which tends to preclude detection of low abundance chemicals and chemicals found in small subsets of samples. The present study provides software to enhance such algorithms for feature detection, quality assessment, and annotation. xMSanalyzer is a set of utilities for automated processing of metabolomics data. The utilites can be classified into four main modules to: 1) improve feature detection for replicate analyses by systematic re-extraction with multiple parameter settings and data merger to optimize the balance between sensitivity and reliability, 2) evaluate sample quality and feature consistency, 3) detect feature overlap between datasets, and 4) characterize high-resolution m/z matches to small molecule metabolites and biological pathways using multiple chemical databases. The package was tested with plasma samples and shown to more than double the number of features extracted while improving quantitative reliability of detection. MS/MS analysis of a random subset of peaks that were exclusively detected using xMSanalyzer confirmed that the optimization scheme improves detection of real metabolites. xMSanalyzer is a package of utilities for data extraction, quality control assessment, detection of overlapping and unique metabolites in multiple datasets, and batch annotation of metabolites. The program was designed to integrate with existing packages such as apLCMS and XCMS, but the framework can also be used to enhance data extraction for other LC/MS data software.

  2. New approaches for metabolomics by mass spectrometry

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Vertes, Akos

    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 domore » 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

  3. HMDB 4.0: the human metabolome database for 2018

    PubMed Central

    Feunang, Yannick Djoumbou; Marcu, Ana; Guo, An Chi; Liang, Kevin; Vázquez-Fresno, Rosa; Sajed, Tanvir; Johnson, Daniel; Li, Carin; Karu, Naama; Sayeeda, Zinat; Lo, Elvis; Assempour, Nazanin; Berjanskii, Mark; Singhal, Sandeep; Arndt, David; Liang, Yonjie; Badran, Hasan; Grant, Jason; Serra-Cayuela, Arnau; Liu, Yifeng; Mandal, Rupa; Neveu, Vanessa; Pon, Allison; Knox, Craig; Wilson, Michael; Manach, Claudine; Scalbert, Augustin

    2018-01-01

    Abstract The Human Metabolome Database or HMDB (www.hmdb.ca) is a web-enabled metabolomic database containing comprehensive information about human metabolites along with their biological roles, physiological concentrations, disease associations, chemical reactions, metabolic pathways, and reference spectra. First described in 2007, the HMDB is now considered the standard metabolomic resource for human metabolic studies. Over the past decade the HMDB has continued to grow and evolve in response to emerging needs for metabolomics researchers and continuing changes in web standards. This year's update, HMDB 4.0, represents the most significant upgrade to the database in its history. For instance, the number of fully annotated metabolites has increased by nearly threefold, the number of experimental spectra has grown by almost fourfold and the number of illustrated metabolic pathways has grown by a factor of almost 60. Significant improvements have also been made to the HMDB’s chemical taxonomy, chemical ontology, spectral viewing, and spectral/text searching tools. A great deal of brand new data has also been added to HMDB 4.0. This includes large quantities of predicted MS/MS and GC–MS reference spectral data as well as predicted (physiologically feasible) metabolite structures to facilitate novel metabolite identification. Additional information on metabolite-SNP interactions and the influence of drugs on metabolite levels (pharmacometabolomics) has also been added. Many other important improvements in the content, the interface, and the performance of the HMDB website have been made and these should greatly enhance its ease of use and its potential applications in nutrition, biochemistry, clinical chemistry, clinical genetics, medicine, and metabolomics science. PMID:29140435

  4. Menthol smokers: metabolomic profiling and smoking behavior

    PubMed Central

    Hsu, Ping-Ching; Lan, Renny S.; Brasky, Theodore M.; Marian, Catalin; Cheema, Amrita K.; Ressom, Habtom W.; Loffredo, Christopher A.; Pickworth, Wallace B.; Shields, Peter G.

    2016-01-01

    Background The use of menthol in cigarettes and marketing is under consideration for regulation by the FDA. However, the effects of menthol on smoking behavior and carcinogen exposure have been inconclusive. We previously reported metabolomic profiling for cigarette smokers, and novelly identified a menthol-glucuronide (MG) as the most significant metabolite directly related to smoking. Here, MG is studied in relation to smoking behavior and metabolomic profiles. Methods A cross-sectional study of 105 smokers who smoked two cigarettes in the laboratory one hour apart. Blood nicotine, MG and exhaled carbon monoxide (CO) boosts were determined (the difference before and after smoking). Spearman's correlation, Chi-Square and ANCOVA adjusted for gender, race and cotinine levels for menthol smokers assessed the relationship of MG boost, smoking behavior, and metabolic profiles. Multivariate metabolite characterization using supervised Partial Least Squares-Discriminant Analysis (PLS-DA) was carried out for the classification of metabolomics profiles. Results MG boost was positively correlated with CO boost, nicotine boost, average puff volume, puff duration, and total smoke exposure. Classification using PLS-DA, MG was the top metabolite discriminating metabolome of menthol vs. non-menthol smokers. Among menthol smokers, forty-two metabolites were significantly correlated with MG boost, which linked to cellular functions such as of cell death, survival, and movement. Conclusion Plasma MG boost is a new smoking behavior biomarker that may provides novel information over self-reported use of menthol cigarettes by integrating different smoking measures for understanding smoking behavior and harm of menthol cigarettes. Impacts These results provide insight into the biological effect of menthol smoking. PMID:27628308

  5. CRAFT (complete reduction to amplitude frequency table)--robust and time-efficient Bayesian approach for quantitative mixture analysis by NMR.

    PubMed

    Krishnamurthy, Krish

    2013-12-01

    The intrinsic quantitative nature of NMR is increasingly exploited in areas ranging from complex mixture analysis (as in metabolomics and reaction monitoring) to quality assurance/control. Complex NMR spectra are more common than not, and therefore, extraction of quantitative information generally involves significant prior knowledge and/or operator interaction to characterize resonances of interest. Moreover, in most NMR-based metabolomic experiments, the signals from metabolites are normally present as a mixture of overlapping resonances, making quantification difficult. Time-domain Bayesian approaches have been reported to be better than conventional frequency-domain analysis at identifying subtle changes in signal amplitude. We discuss an approach that exploits Bayesian analysis to achieve a complete reduction to amplitude frequency table (CRAFT) in an automated and time-efficient fashion - thus converting the time-domain FID to a frequency-amplitude table. CRAFT uses a two-step approach to FID analysis. First, the FID is digitally filtered and downsampled to several sub FIDs, and secondly, these sub FIDs are then modeled as sums of decaying sinusoids using the Bayesian approach. CRAFT tables can be used for further data mining of quantitative information using fingerprint chemical shifts of compounds of interest and/or statistical analysis of modulation of chemical quantity in a biological study (metabolomics) or process study (reaction monitoring) or quality assurance/control. The basic principles behind this approach as well as results to evaluate the effectiveness of this approach in mixture analysis are presented. Copyright © 2013 John Wiley & Sons, Ltd.

  6. Metabolomic Profiles of Current Cigarette Smokers

    PubMed Central

    Hsu, Ping-Ching; Lan, Renny S.; Brasky, Theodore M.; Marian, Catalin; Cheema, Amrita K.; Ressom, Habtom W.; Loffredo, Christopher A.; Pickworth, Wallace B.; Shields, Peter G.

    2017-01-01

    Smoking-related biomarkers for lung cancer and other diseases are needed to enhance early detection strategies and to provide a science base for tobacco product regulation. An untargeted metabolomics approach by ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry (UHPLC-Q-TOF MS) totaling 957 assays was used in a novel experimental design where 105 current smokers smoked 2 cigarettes one hour apart. Blood was collected immediately before and after each cigarette allowing for within-subject replication. Dynamic changes of the metabolomic profiles from smokers’ four blood samples were observed and biomarkers affected by cigarette smoking were identified. Thirty-one metabolites were definitively shown to be affected by acute effect of cigarette smoking, uniquely including menthol-glucuronide, the reduction of glutamate, oleamide, and 13 glycerophospholipids. This first time identification of a menthol metabolite in smokers’ blood serves as proof-of-principle for using metabolomics to identify new tobacco-exposure biomarkers, and also provides new opportunities in studying menthol-containing tobacco products in humans. Gender and race differences also were observed. Network analysis revealed 12 molecules involved in cancer, notably inhibition of cAMP. These novel tobacco-related biomarkers provide new insights to the effects of smoking which may be important in carcinogenesis but not previously linked with tobacco-related diseases. PMID:27341184

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

    PubMed

    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

  8. Proteomics and Metabolomics: Two Emerging Areas for Legume Improvement

    PubMed Central

    Ramalingam, Abirami; Kudapa, Himabindu; Pazhamala, Lekha T.; Weckwerth, Wolfram; Varshney, Rajeev K.

    2015-01-01

    The crop legumes such as chickpea, common bean, cowpea, peanut, pigeonpea, soybean, etc. are important sources 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 signaling 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 signaling in legumes. In this review, several

  9. Recent Progress in the Development of Metabolome Databases for Plant Systems Biology

    PubMed Central

    Fukushima, Atsushi; Kusano, Miyako

    2013-01-01

    Metabolomics has grown greatly as a functional genomics tool, and has become an invaluable diagnostic tool for biochemical phenotyping of biological systems. Over the past decades, a number of databases involving information related to mass spectra, compound names and structures, statistical/mathematical models and metabolic pathways, and metabolite profile data have been developed. Such databases complement each other and support efficient growth in this area, although the data resources remain scattered across the World Wide Web. Here, we review available metabolome databases and summarize the present status of development of related tools, particularly focusing on the plant metabolome. Data sharing discussed here will pave way for the robust interpretation of metabolomic data and advances in plant systems biology. PMID:23577015

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

    PubMed Central

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

    2016-01-01

    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. PMID:27643760

  11. Metabolic pathway engineering based on metabolomics confers acetic and formic acid tolerance to a recombinant xylose-fermenting strain of Saccharomyces cerevisiae

    PubMed Central

    2011-01-01

    Background The development of novel yeast strains with increased tolerance toward inhibitors in lignocellulosic hydrolysates is highly desirable for the production of bio-ethanol. Weak organic acids such as acetic and formic acids are necessarily released during the pretreatment (i.e. solubilization and hydrolysis) of lignocelluloses, which negatively affect microbial growth and ethanol production. However, since the mode of toxicity is complicated, genetic engineering strategies addressing yeast tolerance to weak organic acids have been rare. Thus, enhanced basic research is expected to identify target genes for improved weak acid tolerance. Results In this study, the effect of acetic acid on xylose fermentation was analyzed by examining metabolite profiles in a recombinant xylose-fermenting strain of Saccharomyces cerevisiae. Metabolome analysis revealed that metabolites involved in the non-oxidative pentose phosphate pathway (PPP) [e.g. sedoheptulose-7-phosphate, ribulose-5-phosphate, ribose-5-phosphate and erythrose-4-phosphate] were significantly accumulated by the addition of acetate, indicating the possibility that acetic acid slows down the flux of the pathway. Accordingly, a gene encoding a PPP-related enzyme, transaldolase or transketolase, was overexpressed in the xylose-fermenting yeast, which successfully conferred increased ethanol productivity in the presence of acetic and formic acid. Conclusions Our metabolomic approach revealed one of the molecular events underlying the response to acetic acid and focuses attention on the non-oxidative PPP as a target for metabolic engineering. An important challenge for metabolic engineering is identification of gene targets that have material importance. This study has demonstrated that metabolomics is a powerful tool to develop rational strategies to confer tolerance to stress through genetic engineering. PMID:21219616

  12. SuperTarget goes quantitative: update on drug–target interactions

    PubMed Central

    Hecker, Nikolai; Ahmed, Jessica; von Eichborn, Joachim; Dunkel, Mathias; Macha, Karel; Eckert, Andreas; Gilson, Michael K.; Bourne, Philip E.; Preissner, Robert

    2012-01-01

    There are at least two good reasons for the on-going interest in drug–target interactions: first, drug-effects can only be fully understood by considering a complex network of interactions to multiple targets (so-called off-target effects) including metabolic and signaling pathways; second, it is crucial to consider drug-target-pathway relations for the identification of novel targets for drug development. To address this on-going need, we have developed a web-based data warehouse named SuperTarget, which integrates drug-related information associated with medical indications, adverse drug effects, drug metabolism, pathways and Gene Ontology (GO) terms for target proteins. At present, the updated database contains >6000 target proteins, which are annotated with >330 000 relations to 196 000 compounds (including approved drugs); the vast majority of interactions include binding affinities and pointers to the respective literature sources. The user interface provides tools for drug screening and target similarity inclusion. A query interface enables the user to pose complex queries, for example, to find drugs that target a certain pathway, interacting drugs that are metabolized by the same cytochrome P450 or drugs that target proteins within a certain affinity range. SuperTarget is available at http://bioinformatics.charite.de/supertarget. PMID:22067455

  13. Bioengineering Silicon Quantum Dot Theranostics using a Network Analysis of Metabolomic and Proteomic Data in Cardiac Ischemia

    PubMed Central

    Erogbogbo, Folarin; May, Jasmine; Swihart, Mark; Prasad, Paras N.; Smart, Katie; Jack, Seif El; Korcyk, Dariusz; Webster, Mark; Stewart, Ralph; Zeng, Irene; Jullig, Mia; Bakeev, Katherine; Jamieson, Michelle; Kasabov, Nikolas; Gopalan, Banu; Liang, Linda; Hu, Raphael; Schliebs, Stefan; Villas-Boas, Silas; Gladding, Patrick

    2013-01-01

    Metabolomic profiling is ideally suited for the analysis of cardiac metabolism in healthy and diseased states. Here, we show that systematic discovery of biomarkers of ischemic preconditioning using metabolomics can be translated to potential nanotheranostics. Thirty-three patients underwent percutaneous coronary intervention (PCI) after myocardial infarction. Blood was sampled from catheters in the coronary sinus, aorta and femoral vein before coronary occlusion and 20 minutes after one minute of coronary occlusion. Plasma was analysed using GC-MS metabolomics and iTRAQ LC-MS/MS proteomics. Proteins and metabolites were mapped into the Metacore network database (GeneGo, MI, USA) to establish functional relevance. Expression of 13 proteins was significantly different (p<0.05) as a result of PCI. Included amongst these was CD44, a cell surface marker of reperfusion injury. Thirty-eight metabolites were identified using a targeted approach. Using PCA, 42% of their variance was accounted for by 21 metabolites. Multiple metabolic pathways and potential biomarkers of cardiac ischemia, reperfusion and preconditioning were identified. CD44, a marker of reperfusion injury, and myristic acid, a potential preconditioning agent, were incorporated into a nanotheranostic that may be useful for cardiovascular applications. Integrating biomarker discovery techniques into rationally designed nanoconstructs may lead to improvements in disease-specific diagnosis and treatment. PMID:24019856

  14. Global and targeted metabolomics of esophageal squamous cell carcinoma discovers potential diagnostic and therapeutic biomarkers.

    PubMed

    Xu, Jing; Chen, Yanhua; Zhang, Ruiping; Song, Yongmei; Cao, Jianzhong; Bi, Nan; Wang, Jingbo; He, Jiuming; Bai, Jinfa; Dong, Lijia; Wang, Luhua; Zhan, Qimin; Abliz, Zeper

    2013-05-01

    Diagnostic and therapeutic biomarkers useful for esophageal squamous cell carcinoma (ESCC) have the ability to increase the long term survival of cancer patients. A metabolomics study, using plasma from four groups including ESCC patients before, during, and after chemoradiotherapy (CRT) and healthy controls, was originally carried out by LC-MS to determine global alterations in the metabolic profiles and find biomarkers potentially applicable to diagnosis and monitoring treatment effects. It is worth pointing out that a clear clustering and separation of metabolic data from the four groups was observed, which indicated that disease status and treatment intervention resulted in specific metabolic perturbations in the patients. A series of metabolites were found to be significantly altered in ESCC patients versus healthy controls and in pre- versus post-treatment patients based on multivariate statistical data analysis (MVDA). To further validate the reliability of these potential biomarkers, an independent validation was performed by using the selected reaction monitoring (SRM) based targeted approach. Finally, 18 most significantly altered plasma metabolites in ESCC patients, relative to healthy controls, were tentatively identified as lysophosphatidylcholines (lysoPCs), fatty acids, l-carnitine, acylcarnitines, organic acids, and a sterol metabolite. The classification performance of these metabolites were analyzed by receiver operating characteristic (ROC)(1) analysis and a biomarker panel was generated. Together, biological significance of these metabolites was discussed. Comparison between pre- and post-treatment patients generated 11 metabolites as potential therapeutic biomarkers that were tentatively identified as amino acids, acylcarnitines, and lysoPCs. Levels of three of these (octanoylcarnitine, lysoPC(16:1), and decanoylcarnitine) were closely correlated with treatment effect. Moreover, variation of these three potential biomarkers was investigated

  15. NMR-BASED METABOLOMIC STUDIES OF ENDOCRINE DISRUPTION IN SMALL FISH MODELS

    EPA Science Inventory

    Metabolomics is now being widely used to obtain complementary information to genomic and proteomic studies. Among the various approaches used in metabolomics, NMR spectroscopy is particularly powerful, in part because it is relatively non-selective, and is amenable to the study o...

  16. Lactation is associated with altered metabolomic signatures in women with gestational diabetes.

    PubMed

    Much, Daniela; Beyerlein, Andreas; Kindt, Alida; Krumsiek, Jan; Stückler, Ferdinand; Rossbauer, Michaela; Hofelich, Anna; Wiesenäcker, David; Hivner, Susanne; Herbst, Melanie; Römisch-Margl, Werner; Prehn, Cornelia; Adamski, Jerzy; Kastenmüller, Gabi; Theis, Fabian; Ziegler, Anette-G; Hummel, Sandra

    2016-10-01

    Lactation for >3 months in women with gestational diabetes is associated with a reduced risk of type 2 diabetes that persists for up to 15 years postpartum. However, the underlying mechanisms are unknown. We examined whether in women with gestational diabetes lactation for >3 months is associated with altered metabolomic signatures postpartum. We enrolled 197 women with gestational diabetes at a median of 3.6 years (interquartile range 0.7-6.5 years) after delivery. Targeted metabolomics profiles (including 156 metabolites) were obtained during a glucose challenge test. Comparisons of metabolite concentrations and ratios between women who lactated for >3 months and women who lactated for ≤3 months or not at all were performed using linear regression with adjustment for age and BMI at the postpartum visit, time since delivery, and maternal education level, and correction for multiple testing. Gaussian graphical modelling was used to generate metabolite networks. Lactation for >3 months was associated with a higher total lysophosphatidylcholine/total phosphatidylcholine ratio; in women with short-term follow-up, it was also associated with lower leucine concentrations and a lower total branched-chain amino acid concentration. Gaussian graphical modelling identified subgroups of closely linked metabolites within phosphatidylcholines and branched-chain amino acids that were affected by lactation for >3 months and have been linked to the pathophysiology of type 2 diabetes in previous studies. Lactation for >3 months in women with gestational diabetes is associated with changes in the metabolomics profile that have been linked to the early pathogenesis of type 2 diabetes.

  17. Development of an Integrated Metabolomic Profiling Approach for Infectious Diseases Research

    PubMed Central

    Lv, Haitao; Hung, Chia S.; Chaturvedi, Kaveri S.; Hooton, Thomas M.; Henderson, Jeffrey P.

    2013-01-01

    Metabolomic profiling offers direct insights into the chemical environment and metabolic pathway activities at sites of human disease. During infection, this environment may receive important contributions from both host and pathogen. Here we apply untargeted metabolomics approach to identify compounds associated with an E. coli urinary tract infection population. Correlative and structural data from minimally processed samples were obtained using an optimized LC-MS platform capable of resolving ∼2300 molecular features. Principal components analysis readily distinguished patient groups and multiple supervised chemometric analyses resolved robust metabolomic shifts between groups. These analyses revealed nine compounds whose provisional structures suggest candidate infection-associated endocrine, catabolic, and lipid pathways. Several of these metabolite signatures may derive from microbial processing of host metabolites. Overall, this study highlights the ability of metabolomic approaches to directly identify compounds encountered by, and produced from, bacterial pathogens within human hosts. PMID:21922104

  18. Global Metabolomic Identification of Long-Term Dose-Dependent Urinary Biomarkers in Nonhuman Primates Exposed to Ionizing Radiation.

    PubMed

    Pannkuk, Evan L; Laiakis, Evagelia C; Authier, Simon; Wong, Karen; Fornace, Albert J

    2015-08-01

    Due to concerns surrounding potential large-scale radiological events, there is a need to determine robust radiation signatures for the rapid identification of exposed individuals, which can then be used to guide the development of compact field deployable instruments to assess individual dose. Metabolomics provides a technology to process easily accessible biofluids and determine rigorous quantitative radiation biomarkers with mass spectrometry (MS) platforms. While multiple studies have utilized murine models to determine radiation biomarkers, limited studies have profiled nonhuman primate (NHP) metabolic radiation signatures. In addition, these studies have concentrated on short-term biomarkers (i.e., <72 h). The current study addresses the need for biomarkers beyond 72 h using a NHP model. Urine samples were collected at 7 days postirradiation (2, 4, 6, 7 and 10 Gy) and processed with ultra-performance liquid chromatography (UPLC) quadrupole time-of-flight (QTOF) MS, acquiring global metabolomic radiation signatures. Multivariate data analysis revealed clear separation between control and irradiated groups. Thirteen biomarkers exhibiting a dose response were validated with tandem MS. There was significantly higher excretion of l-carnitine, l-acetylcarnitine, xanthine and xanthosine in males versus females. Metabolites validated in this study suggest perturbation of several pathways including fatty acid β oxidation, tryptophan metabolism, purine catabolism, taurine metabolism and steroid hormone biosynthesis. In this novel study we detected long-term biomarkers in a NHP model after exposure to radiation and demonstrate differences between sexes using UPLC-QTOF-MS-based metabolomics technology.

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

    PubMed Central

    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. PMID:27507964

  20. Plant metabolomics: from holistic hope, to hype, to hot topic.

    PubMed

    Hall, Robert D

    2006-01-01

    In a short time, plant metabolomics has gone from being just an ambitious concept to being a rapidly growing, valuable technology applied in the stride to gain a more global picture of the molecular organization of multicellular organisms. The combination of improved analytical capabilities with newly designed, dedicated statistical, bioinformatics and data mining strategies, is beginning to broaden the horizons of our understanding of how plants are organized and how metabolism is both controlled but highly flexible. Metabolomics is predicted to play a significant, if not indispensable role in bridging the phenotype-genotype gap and thus in assisting us in our desire for full genome sequence annotation as part of the quest to link gene to function. Plants are a fabulously rich source of diverse functional biochemicals and metabolomics is also already proving valuable in an applied context. By creating unique opportunities for us to interrogate plant systems and characterize their biochemical composition, metabolomics will greatly assist in identifying and defining much of the still unexploited biodiversity available today.

  1. Metabolomics of human brain aging and age-related neurodegenerative diseases.

    PubMed

    Jové, Mariona; Portero-Otín, Manuel; Naudí, Alba; Ferrer, Isidre; Pamplona, Reinald

    2014-07-01

    Neurons in the mature human central nervous system (CNS) perform a wide range of motor, sensory, regulatory, behavioral, and cognitive functions. Such diverse functional output requires a great diversity of CNS neuronal and non-neuronal populations. Metabolomics encompasses the study of the complete set of metabolites/low-molecular-weight intermediates (metabolome), which are context-dependent and vary according to the physiology, developmental state, or pathologic state of the cell, tissue, organ, or organism. Therefore, the use of metabolomics can help to unravel the diversity-and to disclose the specificity-of metabolic traits and their alterations in the brain and in fluids such as cerebrospinal fluid and plasma, thus helping to uncover potential biomarkers of aging and neurodegenerative diseases. Here, we review the current applications of metabolomics in studies of CNS aging and certain age-related neurodegenerative diseases such as Alzheimer disease, Parkinson disease, and amyotrophic lateral sclerosis. Neurometabolomics will increase knowledge of the physiologic and pathologic functions of neural cells and will place the concept of selective neuronal vulnerability in a metabolic context.

  2. Capillary electrophoresis - Mass spectrometry metabolomics analysis revealed enrichment of hypotaurine in rat glioma tissues.

    PubMed

    Gao, Peng; Ji, Min; Fang, Xueyan; Liu, Yingyang; Yu, Zhigang; Cao, Yunfeng; Sun, Aijun; Zhao, Liang; Zhang, Yong

    2017-11-15

    Glioma is one of the most lethal brain malignancies with unknown etiologies. Many metabolomics analysis aiming at diverse kinds of samples had been performed. Due to the varied adopted analytical platforms, the reported disease-related metabolites were not consistent across different studies. Comparable metabolomics results are more likely to be acquired by analyzing the same sample types with identical analytical platform. For tumor researches, tissue samples metabolomics analysis own the unique advantage that it can gain more direct insight into disease-specific pathological molecules. In this light, a previous reported capillary electrophoresis - mass spectrometry human tissues metabolomics analysis method was employed to profile the metabolome of rat C6 cell implantation gliomas and the corresponding precancerous tissues. It was found that 9 metabolites increased in the glioma tissues. Of them, hypotaurine was the only metabolite that enriched in the malignant tissues as what had been reported in the relevant human tissues metabolomics analysis. Furthermore, hypotaurine was also proved to inhibit α-ketoglutarate-dependent dioxygenases (2-KDDs) through immunocytochemistry staining and in vitro enzymatic activity assays by using C6 cell cultures. This study reinforced the previous conclusion that hypotaurine acted as a competitive inhibitor of 2-KDDs and proved the value of metabolomics in oncology studies. Copyright © 2017. Published by Elsevier Inc.

  3. Systematic evaluation of serum and plasma collection on the endogenous metabolome.

    PubMed

    Zhou, Zhi; Chen, Yanhua; He, Jiuming; Xu, Jing; Zhang, Ruiping; Mao, Yan; Abliz, Zeper

    2017-02-01

    In metabolomics research, the use of different blood collection methods may influence endogenous metabolites. Ultra HPLC coupled with MS/MS was applied together with multivariate statistics to investigate metabolomics differences in serum and plasma samples handled by different anticoagulants. A total of 135 known representative metabolites were assessed for comprehensive evaluation of the effects of anticoagulants. Exogenous factors, including separation gel ingredients from the serum collection tubes and the anticoagulants, affected mass spectrometer detection. Heparin plasma yielded the best detection of different functional groups and is therefore the optimal blood specimen for metabolomics research, followed by potassium oxalate plasma.

  4. Quantitative changes in proteins responsible for flavonoid and anthocyanin biosynthesis in strawberry fruit at different ripening stages: A targeted quantitative proteomic investigation employing multiple reaction monitoring.

    PubMed

    Song, Jun; Du, Lina; Li, Li; Kalt, Wilhelmina; Palmer, Leslie Campbell; Fillmore, Sherry; Zhang, Ying; Zhang, ZhaoQi; Li, XiHong

    2015-06-03

    To better understand the regulation of flavonoid and anthocyanin biosynthesis, a targeted quantitative proteomic investigation employing LC-MS with multiple reaction monitoring was conducted on two strawberry cultivars at three ripening stages. This quantitative proteomic workflow was improved through an OFFGEL electrophoresis to fractionate peptides from total protein digests. A total of 154 peptide transitions from 47 peptides covering 21 proteins and isoforms related to anthocyanin biosynthesis were investigated. The normalized protein abundance, which was measured using isotopically-labeled standards, was significantly changed concurrently with increased anthocyanin content and advanced fruit maturity. The protein abundance of phenylalanine ammonia-lyase; anthocyanidin synthase, chalcone isomerase; flavanone 3-hydroxylase; dihydroflavonol 4-reductase, UDP-glucose:flavonoid-3-O-glucosyltransferase, cytochrome c and cytochrome C oxidase subunit 2, was all significantly increased in fruit of more advanced ripeness. An interaction between cultivar and maturity was also shown with respect to chalcone isomerase. The good correlation between protein abundance and anthocyanin content suggested that a metabolic control point may exist for anthocyanin biosynthesis. This research provides insights into the process of anthocyanin formation in strawberry fruit at the level of protein concentration and reveals possible candidates in the regulation of anthocyanin formation during fruit ripening. To gain insight into the molecular mechanisms contributing to flavonoids and anthocyanin biosynthesis and regulation of strawberry fruit during ripening is challenging due to limited molecular biology tools and established hypothesis. Our targeted proteomic approach employing LC-MS/MS analysis and MRM technique to quantify proteins in relation to flavonoids and anthocyanin biosynthesis and regulation in strawberry fruit during fruit ripening is novel. The identification of peptides

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

    PubMed

    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.

  6. Women with preterm birth have a distinct cervicovaginal metabolome.

    PubMed

    Ghartey, Jeny; Bastek, Jamie A; Brown, Amy G; Anglim, Laura; Elovitz, Michal A

    2015-06-01

    Metabolomics has the potential to reveal novel pathways involved in the pathogenesis of preterm birth (PTB). The objective of this study was to investigate whether the cervicovaginal (CV) metabolome was different in asymptomatic women destined to have a PTB compared with term birth. A nested case-control study was performed using CV fluid collected from a larger prospective cohort. The CV fluid was collected between 20-24 weeks (V1) and 24-28 weeks (V2). The metabolome was compared between women with a spontaneous PTB (n = 10) to women who delivered at term (n = 10). Samples were extracted and prepared for analysis using a standard extraction solvent method. Global biochemical profiles were determined using gas chromatography/mass spectrometry and ultra-performance liquid chromatography/tandem mass spectrometry. An ANOVA was used to detect differences in biochemical compounds between the groups. A false discovery rate was estimated to account for multiple comparisons. A total of 313 biochemicals were identified in CV fluid. Eighty-two biochemicals were different in the CV fluid at V1 in those destined to have a PTB compared with term birth, whereas 48 were different at V2. Amino acid, carbohydrate, and peptide metabolites were distinct between women with and without PTB. These data suggest that the CV space is metabolically active during pregnancy. Changes in the CV metabolome may be observed weeks, if not months, prior to any clinical symptoms. Understanding the CV metabolome may hold promise for unraveling the pathogenesis of PTB and may provide novel biomarkers to identify women most at risk. Copyright © 2015 Elsevier Inc. All rights reserved.

  7. HMDB 4.0: the human metabolome database for 2018.

    PubMed

    Wishart, David S; Feunang, Yannick Djoumbou; Marcu, Ana; Guo, An Chi; Liang, Kevin; Vázquez-Fresno, Rosa; Sajed, Tanvir; Johnson, Daniel; Li, Carin; Karu, Naama; Sayeeda, Zinat; Lo, Elvis; Assempour, Nazanin; Berjanskii, Mark; Singhal, Sandeep; Arndt, David; Liang, Yonjie; Badran, Hasan; Grant, Jason; Serra-Cayuela, Arnau; Liu, Yifeng; Mandal, Rupa; Neveu, Vanessa; Pon, Allison; Knox, Craig; Wilson, Michael; Manach, Claudine; Scalbert, Augustin

    2018-01-04

    The Human Metabolome Database or HMDB (www.hmdb.ca) is a web-enabled metabolomic database containing comprehensive information about human metabolites along with their biological roles, physiological concentrations, disease associations, chemical reactions, metabolic pathways, and reference spectra. First described in 2007, the HMDB is now considered the standard metabolomic resource for human metabolic studies. Over the past decade the HMDB has continued to grow and evolve in response to emerging needs for metabolomics researchers and continuing changes in web standards. This year's update, HMDB 4.0, represents the most significant upgrade to the database in its history. For instance, the number of fully annotated metabolites has increased by nearly threefold, the number of experimental spectra has grown by almost fourfold and the number of illustrated metabolic pathways has grown by a factor of almost 60. Significant improvements have also been made to the HMDB's chemical taxonomy, chemical ontology, spectral viewing, and spectral/text searching tools. A great deal of brand new data has also been added to HMDB 4.0. This includes large quantities of predicted MS/MS and GC-MS reference spectral data as well as predicted (physiologically feasible) metabolite structures to facilitate novel metabolite identification. Additional information on metabolite-SNP interactions and the influence of drugs on metabolite levels (pharmacometabolomics) has also been added. Many other important improvements in the content, the interface, and the performance of the HMDB website have been made and these should greatly enhance its ease of use and its potential applications in nutrition, biochemistry, clinical chemistry, clinical genetics, medicine, and metabolomics science. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

  8. Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis [Combined Proteomics and Metabolomics Analysis Reveals Grade-Dependent Metabolism Pathways in Kidney Cancer

    DOE Office of Scientific and Technical Information (OSTI.GOV)

    Wettersten, Hiromi I.; Hakimi, A. Ari; Morin, Dexter

    Kidney cancer [or renal cell carcinoma (RCC)] is known as “the internist's tumor” because it has protean systemic manifestations, suggesting that it utilizes complex, nonphysiologic metabolic pathways. Given the increasing incidence of this cancer and its lack of effective therapeutic targets, we undertook an extensive analysis of human RCC tissue employing combined grade-dependent proteomics and metabolomics analysis to determine how metabolic reprogramming occurring in this disease allows it to escape available therapeutic approaches. After validation experiments in RCC cell lines that were wild-type or mutant for the Von Hippel–Lindau tumor suppressor, in characterizing higher-grade tumors, we found that the Warburgmore » effect is relatively more prominent at the expense of the tricarboxylic acid cycle and oxidative metabolism in general. Further, we found that the glutamine metabolism pathway acts to inhibit reactive oxygen species, as evidenced by an upregulated glutathione pathway, whereas the β-oxidation pathway is inhibited, leading to increased fatty acylcarnitines. In support of findings from previous urine metabolomics analyses, we also documented tryptophan catabolism associated with immune suppression, which was highly represented in RCC compared with other metabolic pathways. Altogether, our results offer a rationale to evaluate novel antimetabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC« less

  9. Grade-Dependent Metabolic Reprogramming in Kidney Cancer Revealed by Combined Proteomics and Metabolomics Analysis [Combined Proteomics and Metabolomics Analysis Reveals Grade-Dependent Metabolism Pathways in Kidney Cancer

    DOE PAGES

    Wettersten, Hiromi I.; Hakimi, A. Ari; Morin, Dexter; ...

    2015-05-07

    Kidney cancer [or renal cell carcinoma (RCC)] is known as “the internist's tumor” because it has protean systemic manifestations, suggesting that it utilizes complex, nonphysiologic metabolic pathways. Given the increasing incidence of this cancer and its lack of effective therapeutic targets, we undertook an extensive analysis of human RCC tissue employing combined grade-dependent proteomics and metabolomics analysis to determine how metabolic reprogramming occurring in this disease allows it to escape available therapeutic approaches. After validation experiments in RCC cell lines that were wild-type or mutant for the Von Hippel–Lindau tumor suppressor, in characterizing higher-grade tumors, we found that the Warburgmore » effect is relatively more prominent at the expense of the tricarboxylic acid cycle and oxidative metabolism in general. Further, we found that the glutamine metabolism pathway acts to inhibit reactive oxygen species, as evidenced by an upregulated glutathione pathway, whereas the β-oxidation pathway is inhibited, leading to increased fatty acylcarnitines. In support of findings from previous urine metabolomics analyses, we also documented tryptophan catabolism associated with immune suppression, which was highly represented in RCC compared with other metabolic pathways. Altogether, our results offer a rationale to evaluate novel antimetabolic treatment strategies being developed in other disease settings as therapeutic strategies in RCC« less

  10. Metabolomics for organic food authentication: Results from a long-term field study in carrots.

    PubMed

    Cubero-Leon, Elena; De Rudder, Olivier; Maquet, Alain

    2018-01-15

    Increasing demand for organic products and their premium prices make them an attractive target for fraudulent malpractices. In this study, a large-scale comparative metabolomics approach was applied to investigate the effect of the agronomic production system on the metabolite composition of carrots and to build statistical models for prediction purposes. Orthogonal projections to latent structures-discriminant analysis (OPLS-DA) was applied successfully to predict the origin of the agricultural system of the harvested carrots on the basis of features determined by liquid chromatography-mass spectrometry. When the training set used to build the OPLS-DA models contained samples representative of each harvest year, the models were able to classify unknown samples correctly (100% correct classification). If a harvest year was left out of the training sets and used for predictions, the correct classification rates achieved ranged from 76% to 100%. The results therefore highlight the potential of metabolomic fingerprinting for organic food authentication purposes. Copyright © 2017 The Author(s). Published by Elsevier Ltd.. All rights reserved.

  11. Recent Highlights of Metabolomics in Chinese Medicine Syndrome Research

    PubMed Central

    Zhang, Ai-hua; Sun, Hui; Qiu, Shi; Wang, Xi-jun

    2013-01-01

    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. PMID:24302964

  12. Monitoring Ecological Impacts of Environmental Surface Waters using Cell-based Metabolomics

    EPA Science Inventory

    Optimized cell-based metabolomics has been used to study the impacts of contaminants in surface waters on human and fish metabolomes. This method has proven to be resource- and time-effective, as well as sustainable for long term and large scale studies. In the current study, cel...

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

    PubMed

    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.

  14. Characterization of proteomic and metabolomic responses to dietary factors and supplements.

    PubMed

    Astle, John; Ferguson, Jonathan T; German, J Bruce; Harrigan, George G; Kelleher, Neil L; Kodadek, Thomas; Parks, Bryan A; Roth, Michael J; Singletary, Keith W; Wenger, Craig D; Mahady, Gail B

    2007-12-01

    Over the past decade there has been a renewed interest in research and development of both dietary and nutritional supplements. Significant advancements have been made in the scientific assessment of the quality, safety, and efficacy of these products because of the strong interest in and financial support of these projects. As research in both fields continues to advance, opportunities to use new and innovative research technologies and methodologies, such as proteomics and metabolomics, are critical for the future progress of the science. The purpose of the symposium was to begin the process of communicating new innovative proteomic and metabolomic methodologies that may be applied by researchers in both the nutrition and the natural product communities. This symposium highlighted 2 proteomic approaches, protein fingerprinting in complex mixtures with peptoid microarrays and top-down mass spectrometry for annotation of gene products. Likewise, an overview of the methodologies used in metabolomic profiling of natural products was presented, and an illustration of an integrated metabolomics approach in nutrition research was highlighted.

  15. Targeted metabolomics connects thioredoxin-interacting protein (TXNIP) to mitochondrial fuel selection and regulation of specific oxidoreductase enzymes in skeletal muscle.

    PubMed

    DeBalsi, Karen L; Wong, Kari E; Koves, Timothy R; Slentz, Dorothy H; Seiler, Sarah E; Wittmann, April H; Ilkayeva, Olga R; Stevens, Robert D; Perry, Christopher G R; Lark, Daniel S; Hui, Simon T; Szweda, Luke; Neufer, P Darrell; Muoio, Deborah M

    2014-03-21

    Thioredoxin-interacting protein (TXNIP) is an α-arrestin family member involved in redox sensing and metabolic control. Growing evidence links TXNIP to mitochondrial function, but the molecular nature of this relationship has remained poorly defined. Herein, we employed targeted metabolomics and comprehensive bioenergetic analyses to evaluate oxidative metabolism and respiratory kinetics in mouse models of total body (TKO) and skeletal muscle-specific (TXNIP(SKM-/-)) Txnip deficiency. Compared with littermate controls, both TKO and TXNIP(SKM-/-) mice had reduced exercise tolerance in association with muscle-specific impairments in substrate oxidation. Oxidative insufficiencies in TXNIP null muscles were not due to perturbations in mitochondrial mass, the electron transport chain, or emission of reactive oxygen species. Instead, metabolic profiling analyses led to the discovery that TXNIP deficiency causes marked deficits in enzymes required for catabolism of branched chain amino acids, ketones, and lactate, along with more modest reductions in enzymes of β-oxidation and the tricarboxylic acid cycle. The decrements in enzyme activity were accompanied by comparable deficits in protein abundance without changes in mRNA expression, implying dysregulation of protein synthesis or stability. Considering that TXNIP expression increases in response to starvation, diabetes, and exercise, these findings point to a novel role for TXNIP in coordinating mitochondrial fuel switching in response to nutrient availability.

  16. Targeted Metabolomics Connects Thioredoxin-interacting Protein (TXNIP) to Mitochondrial Fuel Selection and Regulation of Specific Oxidoreductase Enzymes in Skeletal Muscle*

    PubMed Central

    DeBalsi, Karen L.; Wong, Kari E.; Koves, Timothy R.; Slentz, Dorothy H.; Seiler, Sarah E.; Wittmann, April H.; Ilkayeva, Olga R.; Stevens, Robert D.; Perry, Christopher G. R.; Lark, Daniel S.; Hui, Simon T.; Szweda, Luke; Neufer, P. Darrell; Muoio, Deborah M.

    2014-01-01

    Thioredoxin-interacting protein (TXNIP) is an α-arrestin family member involved in redox sensing and metabolic control. Growing evidence links TXNIP to mitochondrial function, but the molecular nature of this relationship has remained poorly defined. Herein, we employed targeted metabolomics and comprehensive bioenergetic analyses to evaluate oxidative metabolism and respiratory kinetics in mouse models of total body (TKO) and skeletal muscle-specific (TXNIPSKM−/−) Txnip deficiency. Compared with littermate controls, both TKO and TXNIPSKM−/− mice had reduced exercise tolerance in association with muscle-specific impairments in substrate oxidation. Oxidative insufficiencies in TXNIP null muscles were not due to perturbations in mitochondrial mass, the electron transport chain, or emission of reactive oxygen species. Instead, metabolic profiling analyses led to the discovery that TXNIP deficiency causes marked deficits in enzymes required for catabolism of branched chain amino acids, ketones, and lactate, along with more modest reductions in enzymes of β-oxidation and the tricarboxylic acid cycle. The decrements in enzyme activity were accompanied by comparable deficits in protein abundance without changes in mRNA expression, implying dysregulation of protein synthesis or stability. Considering that TXNIP expression increases in response to starvation, diabetes, and exercise, these findings point to a novel role for TXNIP in coordinating mitochondrial fuel switching in response to nutrient availability. PMID:24482226

  17. Whole grains beyond fibre: what can metabolomics tell us about mechanisms?

    PubMed

    Ross, Alastair B

    2015-08-01

    Dietary fibre alone does not fully explain the frequent association between greater intake of whole grains and reduced risk of disease in observational studies, and other phytochemicals or food structure may also play an important role. For all the observational evidence for the benefits of a whole-grain-rich diet, we have only limited knowledge of the mechanisms behind this reduction in disease risk, aside from the action of specific cereal fibres on reduction of blood cholesterol and the post-prandial glucose peak. Nutritional metabolomics, the global measurement and interpretation of metabolic profiles, assesses the interaction of food with the endogenous gene-protein cascade and the gut microbiome. This approach allows the generation of new hypotheses which account for systemic effects, rather than just focusing on one or two mechanisms or metabolic pathways. To date, animal and human trials using metabolomics to investigate mechanistic changes to metabolism on eating whole grains and cereal fractions have led to new hypotheses around mechanistic effects of whole grains. These include the role of cereals as a major source of dietary glycine betaine, a possible effect on phospholipid synthesis or metabolism, the role of branched-chain amino acids and improvements in insulin sensitivity, and the possibility that whole grains may have an effect on protein metabolism. These hypotheses help explain some of the observed effects of whole grains, although mechanistic studies using stable isotopes and fully quantitative measures are required to confirm these potential mechanisms.

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

    PubMed

    Gonzalez-Franquesa, Alba; Burkart, Alison M; Isganaitis, Elvira; Patti, Mary-Elizabeth

    2016-08-01

    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 and mathematical modeling approaches, have provided the scientific community with new tools to describe the T2D metabolome. The metabolomics signatures associated with T2D and obesity include increased levels of lactate, glycolytic intermediates, branched-chain and aromatic amino acids, and long-chain fatty acids. 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 treatments.

  19. Non-invasive urinary metabolomic profiling discriminates prostate cancer from benign prostatic hyperplasia.

    PubMed

    Pérez-Rambla, Clara; Puchades-Carrasco, Leonor; García-Flores, María; Rubio-Briones, José; López-Guerrero, José Antonio; Pineda-Lucena, Antonio

    2017-01-01

    Prostate cancer (PCa) is one of the most common malignancies in men worldwide. Serum prostate specific antigen (PSA) level has been extensively used as a biomarker to detect PCa. However, PSA is not cancer-specific and various non-malignant conditions, including benign prostatic hyperplasia (BPH), can cause a rise in PSA blood levels, thus leading to many false positive results. In this study, we evaluated the potential of urinary metabolomic profiling for discriminating PCa from BPH. Urine samples from 64 PCa patients and 51 individuals diagnosed with BPH were analysed using 1 H nuclear magnetic resonance ( 1 H-NMR). Comparative analysis of urinary metabolomic profiles was carried out using multivariate and univariate statistical approaches. The urine metabolomic profile of PCa patients is characterised by increased concentrations of branched-chain amino acids (BCAA), glutamate and pseudouridine, and decreased concentrations of glycine, dimethylglycine, fumarate and 4-imidazole-acetate compared with individuals diagnosed with BPH. PCa patients have a specific urinary metabolomic profile. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be useful to discriminate PCa from BPH in a clinical context.

  20. Association of maternal prepregnancy BMI with metabolomic profile across gestation.

    PubMed

    Hellmuth, C; Lindsay, K L; Uhl, O; Buss, C; Wadhwa, P D; Koletzko, B; Entringer, S

    2017-01-01

    Elevated prepregnancy body mass index (pBMI) and excess gestational weight gain (GWG) constitute important prenatal exposures that may program adiposity and disease risk in offspring. The objective of this study is to investigate the influence of pBMI and GWG on the maternal metabolomic profile across pregnancy, and to identify associations with birth weight. This is a longitudinal prospective study of 167 nondiabetic women carrying a singleton pregnancy. Women were recruited between March 2011 and December 2013 from antenatal clinics affiliated to the University of California, Irvine, Medical Center. Seven women were excluded from analyses because of a diagnosis of diabetes during pregnancy. A total of 254 plasma metabolites known to be related to obesity in nonpregnant populations were analyzed in each trimester using targeted metabolomics. The effects of pBMI and GWG on metabolites were tested through linear regression and principle component analysis, adjusting for maternal sociodemographic factors, diet, and insulin resistance. A Bonferroni correction was applied for multiple comparison testing. pBMI was significantly associated with 40 metabolites. Nonesterified fatty acids (NEFA) showed a strong positive association with pBMI, with specificity for mono-unsaturated and omega-6 NEFA. Among phospholipids, sphingomyelins with two double bonds and phosphatidylcholines containing 20:3 fatty acid chain, indicative of omega-6 NEFA, were positively associated with pBMI. Few associations between GWG, quality and quantity of the diet, insulin resistance and the maternal metabolome throughout gestation were detected. NEFA levels in the first and, to a lesser degree, in the second trimester were positively associated with birth weight percentiles. Preconception obesity appears to have a stronger influence on the maternal metabolic milieu than gestational factors such as weight gain, dietary intake and insulin resistance, highlighting the critical importance of