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Sample records for based plant metabolomics

  1. Metabolomics-assisted biotechnological interventions for developing plant-based functional foods and nutraceuticals.

    Science.gov (United States)

    Kumar, Arun; Mosa, Kareem A; Ji, Liyao; Kage, Udaykumar; Dhokane, Dhananjay; Karre, Shailesh; Madalageri, Deepa; Pathania, Neemisha

    2017-03-08

    Today, the dramatic changes in types of food consumed have led to an increased burden of chronic diseases. Therefore, the emphasis of food research is not only to ensure quality food that can supply adequate nutrients to prevent nutrition related diseases, but also to ensure overall physical and mental-health. This has led to the concept of functional foods and nutraceuticals (FFNs), which can be ideally produced and delivered through plants. Metabolomics can help in getting the most relevant functional information, and thus has been considered the greatest -OMICS technology to date. However, metabolomics has not been exploited to the best potential in plant sciences. The technology can be leveraged to identify the health promoting compounds and metabolites that can be used for the development of FFNs. This article reviews (i) plant-based FFNs-related metabolites and their health benefits; (ii) use of different analytic platforms for targeted and non-targeted metabolite profiling along with experimental considerations; (iii) exploitation of metabolomics to develop FFNs in plants using various biotechnological tools; and (iv) potential use of metabolomics in plant breeding. We have also provided some insights into integration of metabolomics with latest genome editing tools for metabolic pathway regulation in plants.

  2. Chemical Composition and Seasonality of Aromatic Mediterranean Plant Species by NMR-Based Metabolomics

    Directory of Open Access Journals (Sweden)

    Monica Scognamiglio

    2015-01-01

    Full Text Available An NMR-based metabolomic approach has been applied to analyse seven aromatic Mediterranean plant species used in traditional cuisine. Based on the ethnobotanical use of these plants, the approach has been employed in order to study the metabolic changes during different seasons. Primary and secondary metabolites have been detected and quantified. Flavonoids (apigenin, quercetin, and kaempferol derivatives and phenylpropanoid derivatives (e.g., chlorogenic and rosmarinic acid are the main identified polyphenols. The richness in these metabolites could explain the biological properties ascribed to these plant species.

  3. Chemical Composition and Seasonality of Aromatic Mediterranean Plant Species by NMR-Based Metabolomics.

    Science.gov (United States)

    Scognamiglio, Monica; D'Abrosca, Brigida; Esposito, Assunta; Fiorentino, Antonio

    2015-01-01

    An NMR-based metabolomic approach has been applied to analyse seven aromatic Mediterranean plant species used in traditional cuisine. Based on the ethnobotanical use of these plants, the approach has been employed in order to study the metabolic changes during different seasons. Primary and secondary metabolites have been detected and quantified. Flavonoids (apigenin, quercetin, and kaempferol derivatives) and phenylpropanoid derivatives (e.g., chlorogenic and rosmarinic acid) are the main identified polyphenols. The richness in these metabolites could explain the biological properties ascribed to these plant species.

  4. MeRy-B, a metabolomic database and knowledge base for exploring plant primary metabolism.

    Science.gov (United States)

    Deborde, Catherine; Jacob, Daniel

    2014-01-01

    Plant primary metabolites are organic compounds that are common to all or most plant species and are essential for plant growth, development, and reproduction. They are intermediates and products of metabolism involved in photosynthesis and other biosynthetic processes. Primary metabolites belong to different compound families, mainly carbohydrates, organic acids, amino acids, nucleotides, fatty acids, steroids, or lipids. Until recently, unlike the Human Metabolome Database ( http://www.hmdb.ca ) dedicated to human metabolism, there was no centralized database or repository dedicated exclusively to the plant kingdom that contained information on metabolites and their concentrations in a detailed experimental context. MeRy-B is the first platform for plant (1)H-NMR metabolomic profiles (MeRy-B, http://bit.ly/meryb ), designed to provide a knowledge base of curated plant profiles and metabolites obtained by NMR, together with the corresponding experimental and analytical metadata. MeRy-B contains lists of plant metabolites, mostly primary metabolites and unknown compounds, with information about experimental conditions, the factors studied, and metabolite concentrations for 19 different plant species (Arabidopsis, broccoli, daphne, grape, maize, barrel clover, melon, Ostreococcus tauri, palm date, palm tree, peach, pine tree, eucalyptus, plantain rice, strawberry, sugar beet, tomato, vanilla), compiled from more than 2,300 annotated NMR profiles for various organs or tissues deposited by 30 different private or public contributors in September 2013. Currently, about half of the data deposited in MeRy-B is publicly available. In this chapter, readers will be shown how to (1) navigate through and retrieve data of publicly available projects on MeRy-B website; (2) visualize lists of experimentally identified metabolites and their concentrations in all plant species present in MeRy-B; (3) get primary metabolite list for a particular plant species in MeRy-B; and for a

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

    Science.gov (United States)

    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.

  6. Metabolomics and bioactive substances in plants

    DEFF Research Database (Denmark)

    Khakimov, Bekzod

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

  7. Plant single-cell and single-cell-type metabolomics.

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    Misra, Biswapriya B; Assmann, Sarah M; Chen, Sixue

    2014-10-01

    In conjunction with genomics, transcriptomics, and proteomics, plant metabolomics is providing large data sets that are paving the way towards a comprehensive and holistic understanding of plant growth, development, defense, and productivity. However, dilution effects from organ- and tissue-based sampling of metabolomes have limited our understanding of the intricate regulation of metabolic pathways and networks at the cellular level. Recent advances in metabolomics methodologies, along with the post-genomic expansion of bioinformatics knowledge and functional genomics tools, have allowed the gathering of enriched information on individual cells and single cell types. Here we review progress, current status, opportunities, and challenges presented by single cell-based metabolomics research in plants. Copyright © 2014 Elsevier Ltd. All rights reserved.

  8. NMR-based milk metabolomics

    DEFF Research Database (Denmark)

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

    2013-01-01

    and processing capabilities of bovine milk is closely associated to milk composition. Metabolomics is ideal in the study of the low-molecular-weight compounds in milk, and this review focuses on the recent nuclear magnetic resonance (NMR)-based metabolomics trends in milk research, including applications linking...... the milk metabolite profiling with nutritional aspects, and applications which aim to link the milk metabolite profile to various technological qualities of milk. The metabolite profiling studies encompass the identification of novel metabolites, which potentially can be used as biomarkers or as bioactive...... compounds. Furthermore, metabolomics applications elucidating how the differential regulated genes affects milk composition are also reported. This review will highlight the recent advances in NMR-based metabolomics on milk, as well as give a brief summary of when NMR spectroscopy can be useful for gaining...

  9. Monolithic silica-based capillary reversed-phase liquid chromatography/electrospray mass spectrometry for plant metabolomics

    NARCIS (Netherlands)

    Tolstikov, V.V.; Lommen, A.; Nakanishi, K.; Tanaka, N.; Fiehn, O.

    2003-01-01

    Application of C18 monolithic silica capillary columns in HPLC coupled to ion trap mass spectrometry detection was studied for probing the metabolome of the model plant Arabidopsis thaliana. It could be shown that the use of a long capillary column is an easy and effective approach to reduce

  10. Metabolomics of forage plants: a review.

    Science.gov (United States)

    Rasmussen, Susanne; Parsons, Anthony J; Jones, Christopher S

    2012-11-01

    Forage plant breeding is under increasing pressure to deliver new cultivars with improved yield, quality and persistence to the pastoral industry. New innovations in DNA sequencing technologies mean that quantitative trait loci analysis and marker-assisted selection approaches are becoming faster and cheaper, and are increasingly used in the breeding process with the aim to speed it up and improve its precision. High-throughput phenotyping is currently a major bottle neck and emerging technologies such as metabolomics are being developed to bridge the gap between genotype and phenotype; metabolomics studies on forages are reviewed in this article. Major challenges for pasture production arise from the reduced availability of resources, mainly water, nitrogen and phosphorus, and metabolomics studies on metabolic responses to these abiotic stresses in Lolium perenne and Lotus species will be discussed here. Many forage plants can be associated with symbiotic microorganisms such as legumes with nitrogen fixing rhizobia, grasses and legumes with phosphorus-solubilizing arbuscular mycorrhizal fungi, and cool temperate grasses with fungal anti-herbivorous alkaloid-producing Neotyphodium endophytes and metabolomics studies have shown that these associations can significantly affect the metabolic composition of forage plants. The combination of genetics and metabolomics, also known as genetical metabolomics can be a powerful tool to identify genetic regions related to specific metabolites or metabolic profiles, but this approach has not been widely adopted for forages yet, and we argue here that more studies are needed to improve our chances of success in forage breeding. Metabolomics combined with other '-omics' technologies and genome sequencing can be invaluable tools for large-scale geno- and phenotyping of breeding populations, although the implementation of these approaches in forage breeding programmes still lags behind. The majority of studies using metabolomics

  11. Plant Metabolomics: An Indispensable System Biology Tool for Plant Science

    Directory of Open Access Journals (Sweden)

    Jun Hong

    2016-06-01

    Full Text Available As genomes of many plant species have been sequenced, demand for functional genomics has dramatically accelerated the improvement of other omics including metabolomics. Despite a large amount of metabolites still remaining to be identified, metabolomics has contributed significantly not only to the understanding of plant physiology and biology from the view of small chemical molecules that reflect the end point of biological activities, but also in past decades to the attempts to improve plant behavior under both normal and stressed conditions. Hereby, we summarize the current knowledge on the genetic and biochemical mechanisms underlying plant growth, development, and stress responses, focusing further on the contributions of metabolomics to practical applications in crop quality improvement and food safety assessment, as well as plant metabolic engineering. We also highlight the current challenges and future perspectives in this inspiring area, with the aim to stimulate further studies leading to better crop improvement of yield and quality.

  12. Plant Metabolomics: An Indispensable System Biology Tool for Plant Science

    Science.gov (United States)

    Hong, Jun; Yang, Litao; Zhang, Dabing; Shi, Jianxin

    2016-01-01

    As genomes of many plant species have been sequenced, demand for functional genomics has dramatically accelerated the improvement of other omics including metabolomics. Despite a large amount of metabolites still remaining to be identified, metabolomics has contributed significantly not only to the understanding of plant physiology and biology from the view of small chemical molecules that reflect the end point of biological activities, but also in past decades to the attempts to improve plant behavior under both normal and stressed conditions. Hereby, we summarize the current knowledge on the genetic and biochemical mechanisms underlying plant growth, development, and stress responses, focusing further on the contributions of metabolomics to practical applications in crop quality improvement and food safety assessment, as well as plant metabolic engineering. We also highlight the current challenges and future perspectives in this inspiring area, with the aim to stimulate further studies leading to better crop improvement of yield and quality. PMID:27258266

  13. Plant Metabolomics: An Indispensable System Biology Tool for Plant Science.

    Science.gov (United States)

    Hong, Jun; Yang, Litao; Zhang, Dabing; Shi, Jianxin

    2016-06-01

    As genomes of many plant species have been sequenced, demand for functional genomics has dramatically accelerated the improvement of other omics including metabolomics. Despite a large amount of metabolites still remaining to be identified, metabolomics has contributed significantly not only to the understanding of plant physiology and biology from the view of small chemical molecules that reflect the end point of biological activities, but also in past decades to the attempts to improve plant behavior under both normal and stressed conditions. Hereby, we summarize the current knowledge on the genetic and biochemical mechanisms underlying plant growth, development, and stress responses, focusing further on the contributions of metabolomics to practical applications in crop quality improvement and food safety assessment, as well as plant metabolic engineering. We also highlight the current challenges and future perspectives in this inspiring area, with the aim to stimulate further studies leading to better crop improvement of yield and quality.

  14. Metabolomics

    DEFF Research Database (Denmark)

    Pedersen, Hans

    is a presentation of a core consistency diagnostic aiding in determining the number of components in a PARAFAC2 model. It is of great importance to validate especially PLS-DA models and if not done properly, the developed models might reveal spurious groupings. Furthermore, data from metabolomics studies contain...... and the results indicate that GC-MS-based metabolomics in combination with PARAFAC2 modelling is applicable for extracting relevant biological information from the plasma samples. Overall, the work in this thesis shows that suitable and properly validated chemometrics models used in metabolomics are very useful...

  15. NMR-based metabolomics applications

    DEFF Research Database (Denmark)

    Iaccarino, Nunzia

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

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

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

    2016-01-01

    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. PMID:27853298

  17. Basics of mass spectrometry based metabolomics.

    Science.gov (United States)

    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.

  18. Medicinal Plants: A Public Resource for Metabolomics and Hypothesis Development

    Directory of Open Access Journals (Sweden)

    Eve Syrkin Wurtele

    2012-11-01

    Full Text Available Specialized compounds from photosynthetic organisms serve as rich resources for drug development. From aspirin to atropine, plant-derived natural products have had a profound impact on human health. Technological advances provide new opportunities to access these natural products in a metabolic context. Here, we describe a database and platform for storing, visualizing and statistically analyzing metabolomics data from fourteen medicinal plant species. The metabolomes and associated transcriptomes (RNAseq for each plant species, gathered from up to twenty tissue/organ samples that have experienced varied growth conditions and developmental histories, were analyzed in parallel. Three case studies illustrate different ways that the data can be integrally used to generate testable hypotheses concerning the biochemistry, phylogeny and natural product diversity of medicinal plants. Deep metabolomics analysis of Camptotheca acuminata exemplifies how such data can be used to inform metabolic understanding of natural product chemical diversity and begin to formulate hypotheses about their biogenesis. Metabolomics data from Prunella vulgaris, a species that contains a wide range of antioxidant, antiviral, tumoricidal and anti-inflammatory constituents, provide a case study of obtaining biosystematic and developmental fingerprint information from metabolite accumulation data in a little studied species. Digitalis purpurea, well known as a source of cardiac glycosides, is used to illustrate how integrating metabolomics and transcriptomics data can lead to identification of candidate genes encoding biosynthetic enzymes in the cardiac glycoside pathway. Medicinal Plant Metabolomics Resource (MPM [1] provides a framework for generating experimentally testable hypotheses about the metabolic networks that lead to the generation of specialized compounds, identifying genes that control their biosynthesis and establishing a basis for modeling metabolism in less

  19. Medicinal plants: a public resource for metabolomics and hypothesis development.

    Science.gov (United States)

    Wurtele, Eve Syrkin; Chappell, Joe; Jones, A Daniel; Celiz, Mary Dawn; Ransom, Nick; Hur, Manhoi; Rizshsky, Ludmila; Crispin, Matthew; Dixon, Philip; Liu, Jia; P Widrlechner, Mark; Nikolau, Basil J

    2012-11-21

    Specialized compounds from photosynthetic organisms serve as rich resources for drug development. From aspirin to atropine, plant-derived natural products have had a profound impact on human health. Technological advances provide new opportunities to access these natural products in a metabolic context. Here, we describe a database and platform for storing, visualizing and statistically analyzing metabolomics data from fourteen medicinal plant species. The metabolomes and associated transcriptomes (RNAseq) for each plant species, gathered from up to twenty tissue/organ samples that have experienced varied growth conditions and developmental histories, were analyzed in parallel. Three case studies illustrate different ways that the data can be integrally used to generate testable hypotheses concerning the biochemistry, phylogeny and natural product diversity of medicinal plants. Deep metabolomics analysis of Camptotheca acuminata exemplifies how such data can be used to inform metabolic understanding of natural product chemical diversity and begin to formulate hypotheses about their biogenesis. Metabolomics data from Prunella vulgaris, a species that contains a wide range of antioxidant, antiviral, tumoricidal and anti-inflammatory constituents, provide a case study of obtaining biosystematic and developmental fingerprint information from metabolite accumulation data in a little studied species. Digitalis purpurea, well known as a source of cardiac glycosides, is used to illustrate how integrating metabolomics and transcriptomics data can lead to identification of candidate genes encoding biosynthetic enzymes in the cardiac glycoside pathway. Medicinal Plant Metabolomics Resource (MPM) [1] provides a framework for generating experimentally testable hypotheses about the metabolic networks that lead to the generation of specialized compounds, identifying genes that control their biosynthesis and establishing a basis for modeling metabolism in less studied species. The

  20. Metabolomics

    DEFF Research Database (Denmark)

    Kamstrup-Nielsen, Maja Hermann

    how to properly handle complex metabolomics data, in order to achieve reliable and valid multivariate models. This has been illustrated by three case studies with examples of forecasting breast cancer and early detection of colorectal cancer based on data from nuclear magnetic resonance (NMR...... based on NMR data with RRV and known risk markers. The sensitivity and specificity values are 0.80 and 0.79, respectively, for a test set validated model. The second case study is based on plasma samples with verified colorectal cancer and three types of control samples analysed by fluorescence...... spectroscopy a potential tool in early detection of colorectal cancer. Finally, plasma samples have been analysed using GC-MS. The method requires extensive sample preparation and therefore the study can only be considered a feasibility study with room for optimization. However, 14 plasma samples were analysed...

  1. Cell-based metabolomics approach for assessing the impact of wastewater treatment plant effluent on downstream water quality

    Science.gov (United States)

    Wastewater treatment plants (WWTP) are a known source of various types of chemicals including pharmaceuticals and personal care products (PPCPs), naturally occurring hormones, and pesticides. There is great concern regarding their adverse effects on human and ecological health th...

  2. Understanding Plant Nitrogen Metabolism through Metabolomics and Computational Approaches

    Directory of Open Access Journals (Sweden)

    Perrin H. Beatty

    2016-10-01

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

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

    Science.gov (United States)

    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

  4. Comparative metabolomics approach coupled with cell- and gene-based assays for species classification and anti-inflammatory bioactivity validation of Echinacea plants.

    Science.gov (United States)

    Hou, Chia-Chung; Chen, Chun-Houh; Yang, Ning-Sun; Chen, Yi-Ping; Lo, Chiu-Ping; Wang, Sheng-Yang; Tien, Yin-Jing; Tsai, Pi-Wen; Shyur, Lie-Fen

    2010-11-01

    Echinacea preparations were the top-selling herbal supplements or medicines in the past decade; however, there is still frequent misidentification or substitution of the Echinacea plant species in the commercial Echinacea products with not well chemically defined compositions in a specific preparation. In this report, a comparative metabolomics study, integrating supercritical fluid extraction, gas chromatography/mass spectrometry and data mining, demonstrates that the three most used medicinal Echinacea species, Echinacea purpurea, E. pallida, and E. angustifolia, can be easily classified by the distribution and relative content of metabolites. A mitogen-induced murine skin inflammation study suggested that alkamides were the active anti-inflammatory components present in Echinacea plants. Mixed alkamides and the major component, dodeca-2E,4E,8Z,10Z(E)-tetraenoic acid isobutylamides, were then isolated from E. purpurea root extracts for further bioactivity elucidation. In macrophages, the alkamides significantly inhibited cyclooxygenase 2 (COX-2) activity and the lipopolysaccharide-induced expression of COX-2, inducible nitric oxide synthase and specific cytokines or chemokines [i.e., TNF-α, interleukin (IL)-1α, IL-6, MCP-1, MIP-1β] but elevated heme oxygenase-1 protein expression. Cichoric acid, however, exhibited little or no effect. The results of high-performance liquid chromatography/electron spray ionization/mass spectrometry metabolite profiling of alkamides and phenolic compounds in E. purpurea roots showed that specific phytocompound (i.e., alkamides, cichoric acid and rutin) contents were subject to change under certain post-harvest or abiotic treatment. This study provides new insight in using the emerging metabolomics approach coupled with bioactivity assays for medicinal/nutritional plant species classification, quality control and the identification of novel botanical agents for inflammatory disorders. Copyright © 2010 Elsevier Inc. All rights

  5. Chemical interactions between plants in Mediterranean vegetation: the influence of selected plant extracts on Aegilops geniculata metabolome.

    Science.gov (United States)

    Scognamiglio, Monica; Fiumano, Vittorio; D'Abrosca, Brigida; Esposito, Assunta; Choi, Young Hae; Verpoorte, Robert; Fiorentino, Antonio

    2014-10-01

    Allelopathy is the chemical mediated communication among plants. While on one hand there is growing interest in the field, on the other hand it is still debated as doubts exist at different levels. A number of compounds have been reported for their ability to influence plant growth, but the existence of this phenomenon in the field has rarely been demonstrated. Furthermore, only few studies have reported the uptake and the effects at molecular level of the allelochemicals. Allelopathy has been reported on some plants of Mediterranean vegetation and could contribute to structuring this ecosystem. Sixteen plants of Mediterranean vegetation have been selected and studied by an NMR-based metabolomics approach. The extracts of these donor plants have been characterized in terms of chemical composition and the effects on a selected receiving plant, Aegilops geniculata, have been studied both at the morphological and at the metabolic level. Most of the plant extracts employed in this study were found to have an activity, which could be correlated with the presence of flavonoids and hydroxycinnamate derivatives. These plant extracts affected the receiving plant in different ways, with different rates of growth inhibition at morphological level. The results of metabolomic analysis of treated plants suggested the induction of oxidative stress in all the receiving plants treated with active donor plant extracts, although differences were observed among the responses. Finally, the uptake and transport into receiving plant leaves of different metabolites present in the extracts added to the culture medium were observed. Copyright © 2014 Elsevier Ltd. All rights reserved.

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

    NARCIS (Netherlands)

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

    2002-01-01

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

  7. A proposed framework for the description of plant metabolomics experiments and their results

    NARCIS (Netherlands)

    Jenkens, H.; Hardy, N.; Beckmann, M.; Draper, J.; Smith, A.R.; Taylor, J.; Fiehn, O.; Goodacre, R.; Bino, R.J.; Hall, R.D.; Kopka, J.; Lane, G.A.; Lange, B.M.; Liu, J.R.; Mendes, P.; Nikolau, B.J.; Oliver, S.G.; Paton, I.R.; Roessner-Tunali, U.; Saito, K.; Smedsgaard, J.; Sumner, L.W.; Wang, T.; Walsh, S.; Wurtele, E.S.; Kell, D.B.

    2004-01-01

    The study of the metabolite complement of biological samples, known as metabolomics, is creating large amounts of data, and support for handling these data sets is required to facilitate meaningful analyses that will answer biological questions. We present a data model for plant metabolomics known

  8. A proposed framework for the description of plant metabolomics experiments and their results

    DEFF Research Database (Denmark)

    Jenkins, H.; Hardy, N.; Beckmann, M-

    2004-01-01

    The study of the metabolite complement of biological samples, known as metabolomics, is creating large amounts of data, and support for handling these data sets is required to facilitate meaningful analyses that will answer biological questions. We present a data model for plant metabolomics known...

  9. Mass spectrometry-based metabolomics for tuberculosis meningitis.

    Science.gov (United States)

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

    2018-04-18

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

  10. Are the metabolomic responses to folivory of closely related plant species linked to macroevolutionary and plant-folivore coevolutionary processes?

    Energy Technology Data Exchange (ETDEWEB)

    Rivas-Ubach, Albert [Environmental Molecular Sciences Laboratory, Pacific Northwest National Laboratory, Richland Washington 99354 USA; CREAF, Cerdanyola del Vallès 08913 Catalonia Spain; Hódar, José A. [Grupo de Ecología Terrestre, Departamento de Biología Animal y Ecología, Facultad de Ciencias, Universidad de Granada, 18071 Granada Spain; Sardans, Jordi [CREAF, Cerdanyola del Vallès 08913 Catalonia Spain; CSIC, Global Ecology Unit CREAF-CEAB-CSIC-UAB, Cerdanyola del Vallès 08913 Catalonia Spain; Kyle, Jennifer E. [Biological Sciences Division, Pacific Northwest National Laboratory, Richland Washington 99354 USA; Kim, Young-Mo [Biological Sciences Division, Pacific Northwest National Laboratory, Richland Washington 99354 USA; Oravec, Michal [Global Change Research Centre, Academy of Sciences of the Czech Republic, Bĕlidla 4a CZ-603 00 Brno Czech Republic; Urban, Otmar [Global Change Research Centre, Academy of Sciences of the Czech Republic, Bĕlidla 4a CZ-603 00 Brno Czech Republic; Guenther, Alex [Department of Earth System Science, University of California, Irvine California 92697 USA; Peñuelas, Josep [CREAF, Cerdanyola del Vallès 08913 Catalonia Spain; CSIC, Global Ecology Unit CREAF-CEAB-CSIC-UAB, Cerdanyola del Vallès 08913 Catalonia Spain

    2016-06-02

    The debate whether the coevolution of plants and insects or macroevolutionary processes (phylogeny) is the main driver determining the arsenal of molecular defensive compounds of plants remains unresolved. Attacks by herbivorous insects affect not only the composition of defensive compounds in plants but the entire metabolome (the set of molecular metabolites), including defensive compounds. Metabolomes are the final products of genotypes and are directly affected by macroevolutionary processes, so closely related species should have similar metabolomic compositions and may respond in similar ways to attacks by folivores. We analyzed the elemental compositions and metabolomes of needles from Pinus pinaster, P. nigra and P. sylvestris to determine if these closely related Pinus species with different coevolutionary histories with the caterpillars of the processionary moth respond similarly to attacks by this lepidopteran. All pines had different metabolomes and metabolic responses to herbivorous attack. The metabolomic variation among the pine species and the responses to folivory reflected their macroevolutionary relationships, with P. pinaster having the most divergent metabolome. The concentrations of phenolic metabolites were generally not higher in the attacked trees, which had lower concentrations of terpenes, suggesting that herbivores avoid individuals with high concentrations of terpenes. Our results suggest that macroevolutionary history plays important roles in the metabolomic responses of these pine species to folivory, but plant-insect coevolution probably constrains those responses. Combinations of different evolutionary factors and trade-offs are likely responsible for the different responses of each species to folivory, which is not necessarily exclusively linked to plant-insect coevolution.

  11. The photographer and the greenhouse: how to analyse plant metabolomics data

    NARCIS (Netherlands)

    Jansen, J.J.; Smit, S.; Hoefsloot, H.C.J.; Smilde, A.K.

    2010-01-01

    ntroduction - Plant metabolomics experiments yield large amounts of data, too much to be interpretable by eye. Multivariate data analyses are therefore essential to extract and visualise the information of interest. Objective - Because multivariate statistical methods may be remote from the

  12. Analyzing metabolomics-based challenge test

    NARCIS (Netherlands)

    Vis, D.J.; Westerhuis, J.A.; Jacobs, D.M.; van Duynhoven, J.P.M.; Wopereis, S.; van Ommen, B.; Hendriks, M.M.W.B.; Smilde, A.K.

    2015-01-01

    Challenge tests are used to assess the resilience of human beings to perturbations by analyzing responses to detect functional abnormalities. Well known examples are allergy tests and glucose tolerance tests. Increasingly, metabolomics analysis of blood or serum samples is used to analyze the

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

    DEFF Research Database (Denmark)

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

    2015-01-01

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

  14. Plant metabolomics and its potential application for human nutrition

    NARCIS (Netherlands)

    Hall, R.D.; Brouwer, I.D.; Fitzgerald, M.A.

    2008-01-01

    With the growing interest in the use of metabolomic technologies for a wide range of biological targets, food applications related to nutrition and quality are rapidly emerging. Metabolomics offers us the opportunity to gain deeper insights into, and have better control of, the fundamental

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

    Directory of Open Access Journals (Sweden)

    Chi Chen

    2013-01-01

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

  16. Metabolomic-based identification of clusters that reflect dietary patterns.

    Science.gov (United States)

    Gibbons, Helena; Carr, Eibhlin; McNulty, Breige A; Nugent, Anne P; Walton, Janette; Flynn, Albert; Gibney, Michael J; Brennan, Lorraine

    2017-10-01

    Classification of subjects into dietary patterns generally relies on self-reporting dietary data which are prone to error. The aim of the present study was to develop a model for objective classification of people into dietary patterns based on metabolomic data. Dietary and urinary metabolomic data from the National Adult Nutrition Survey (NANS) was used in the analysis (n = 567). Two-step cluster analysis was applied to the urinary data to identify clusters. The subsequent model was used in an independent cohort to classify people into dietary patterns. Two distinct dietary patterns were identified. Cluster 1 was characterized by significantly higher intakes of breakfast cereals, low fat and skimmed milks, potatoes, fruit, fish and fish dishes (p patterns based on metabolomics data. Future applications of this approach could be developed for rapid and objective assignment of subjects into dietary patterns. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  17. Novel chemistry of invasive plants: exotic species have more unique metabolomic profiles than native congeners

    NARCIS (Netherlands)

    Macel, M.; de Vos, R.C.H.; Jansen, J.J.; Van der Putten, W.H.; Van Dam, N.M.

    2014-01-01

    t is often assumed that exotic plants can become invasive when they possess novel secondary chemistry compared with native plants in the introduced range. Using untargeted metabolomic fingerprinting, we compared a broad range of metabolites of six successful exotic plant species and their native

  18. Novel chemistry of invasive plants: exotic species have more unique metabolomic profiles than native congeners

    NARCIS (Netherlands)

    Macel, M.; Vos, de R.C.H.; Jansen, J.J.; Putten, van der W.H.; Dam, van N.M.

    2014-01-01

    It is often assumed that exotic plants can become invasive when they possess novel secondary chemistry compared with native plants in the introduced range. Using untargeted metabolomic fingerprinting, we compared a broad range of metabolites of six successful exotic plant species and their native

  19. A liquid chromatography-mass spectrometry-based metabolome database for tomato

    NARCIS (Netherlands)

    Moco, S.I.A.; Bino, R.J.; Vorst, O.F.J.; Verhoeven, H.A.; Groot, de J.C.W.; Beek, van T.A.; Vervoort, J.J.M.; Vos, de C.H.

    2006-01-01

    For the description of the metabolome of an organism, the development of common metabolite databases is of utmost importance. Here we present the Metabolome Tomato Database (MoTo DB), a metabolite database dedicated to liquid chromatography-mass spectrometry (LC-MS)- based metabolomics of tomato

  20. Metabolomic characteristics of Catharanthus roseus plants in time and space

    NARCIS (Netherlands)

    Qifang, Pan; Qifang, Pan

    2014-01-01

    The thesis aims at combining metabolomics with other methods to investigate the regulation of the TIA biosynthesis and how this is connected with other pathways and the plant’s physiology and development. It reviews the biosynthesis studies of Catharanthus roseus. An HPLC method is described for

  1. Plant Metabolomics and Its Potential for Systems Biology Research: Background Concepts, Technology, and Methodology

    NARCIS (Netherlands)

    Allwood, J.W.; Vos, de C.H.; Moing, A.; Deborde, C.; Erban, A.; Kopka, J.; Goodacre, R.; Hall, R.D.

    2011-01-01

    The "metabolome" comprises the entire complement of small molecules in a plant or any other organism. It represents the ultimate phenotype of cells, deduced from the perturbation of gene expression and the modulation of protein function, as well as environmental cues. Extensive advances over the

  2. A metabolomic approach to identify anti-hepatocarcinogenic compounds from plants used traditionally in the treatment of liver diseases.

    Science.gov (United States)

    Chassagne, François; Haddad, Mohamed; Amiel, Aurélien; Phakeovilay, Chiobouaphong; Manithip, Chanthanom; Bourdy, Geneviève; Deharo, Eric; Marti, Guillaume

    2018-02-23

    Liver cancer is a major health burden in Southeast Asia, and most patients turn towards the use of medicinal plants to alleviate their symptoms. The aim of this work was to apply to Southeast Asian plants traditionally used to treat liver disorders, a successive ranking strategy based on a comprehensive review of the literature and metabolomic data in order to relate ethnopharmacological relevance to chemical entities of interest. We analyzed 45 publications resulting in a list of 378 plant species, and our point system based on the frequency of citation in the literature allowed the selection of 10 top ranked species for further collection and extraction. Extracts of these plants were tested for their in vitro anti-proliferative activities on HepG2 cells. Ethanolic extracts of Andrographis paniculata, Oroxylum indicum, Orthosiphon aristatus and Willughbeia edulis showed the highest anti-proliferative effects (IC 50  = 195.9, 64.1, 71.3 and 66.7 μg/ml, respectively). A metabolomic ranking model was performed to annotate compounds responsible for the anti-proliferative properties of A. paniculata (andrographolactone and dehydroandrographolide), O. indicum (baicalein, chrysin, oroxylin A and scutellarein), O. aristatus (5-desmethylsinensetin) and W. edulis (parabaroside C and procyanidin). Overall, our dereplicative approach combined with a bibliographic scoring system allowed us to rapidly decipher the molecular basis of traditionally used medicinal plants. Copyright © 2018 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

    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.

  4. Impact of Soil Warming on the Plant Metabolome of Icelandic Grasslands

    Science.gov (United States)

    Gargallo-Garriga, Albert; Ayala-Roque, Marta; Granda, Victor; Sigurdsson, Bjarni D.; Leblans, Niki I. W.; Oravec, Michal; Urban, Otmar; Janssens, Ivan A.

    2017-01-01

    Climate change is stronger at high than at temperate and tropical latitudes. The natural geothermal conditions in southern Iceland provide an opportunity to study the impact of warming on plants, because of the geothermal bedrock channels that induce stable gradients of soil temperature. We studied two valleys, one where such gradients have been present for centuries (long-term treatment), and another where new gradients were created in 2008 after a shallow crustal earthquake (short-term treatment). We studied the impact of soil warming (0 to +15 °C) on the foliar metabolomes of two common plant species of high northern latitudes: Agrostis capillaris, a monocotyledon grass; and Ranunculus acris, a dicotyledonous herb, and evaluated the dependence of shifts in their metabolomes on the length of the warming treatment. The two species responded differently to warming, depending on the length of exposure. The grass metabolome clearly shifted at the site of long-term warming, but the herb metabolome did not. The main up-regulated compounds at the highest temperatures at the long-term site were saccharides and amino acids, both involved in heat-shock metabolic pathways. Moreover, some secondary metabolites, such as phenolic acids and terpenes, associated with a wide array of stresses, were also up-regulated. Most current climatic models predict an increase in annual average temperature between 2–8 °C over land masses in the Arctic towards the end of this century. The metabolomes of A. capillaris and R. acris shifted abruptly and nonlinearly to soil warming >5 °C above the control temperature for the coming decades. These results thus suggest that a slight warming increase may not imply substantial changes in plant function, but if the temperature rises more than 5 °C, warming may end up triggering metabolic pathways associated with heat stress in some plant species currently dominant in this region. PMID:28832555

  5. Discrimination of conventional and organic white cabbage from a long-term field trial study using untargeted LC-MS-based metabolomics

    DEFF Research Database (Denmark)

    Mie, Axel; Laursen, Kristian Holst; Åberg, K. Magnus

    2014-01-01

    The influence of organic and conventional farming practices on the content of single nutrients in plants is disputed in the scientific literature. Here, large-scale untargeted LC-MS-based metabolomics was used to compare the composition of white cabbage from organic and conventional agriculture...... (p = 0.013) imprint in the white cabbage metabolome that is retained between production years. We externally validated this finding by predicting the production system of samples from one year using a classification model built on samples from the other year, with a correct classification in 83...... % of cases. Thus, it was concluded that the investigated conventional and organic management practices have a systematic impact on the metabolome of white cabbage. This emphasizes the potential of untargeted metabolomics for authenticity testing of organic plant products....

  6. Stable Isotope-Assisted Evaluation of Different Extraction Solvents for Untargeted Metabolomics of Plants

    Directory of Open Access Journals (Sweden)

    Maria Doppler

    2016-06-01

    Full Text Available The evaluation of extraction protocols for untargeted metabolomics approaches is still difficult. We have applied a novel stable isotope-assisted workflow for untargeted LC-HRMS-based plant metabolomics , which allows for the first time every detected feature to be considered for method evaluation. The efficiency and complementarity of commonly used extraction solvents, namely 1 + 3 (v/v mixtures of water and selected organic solvents (methanol, acetonitrile or methanol/acetonitrile 1 + 1 (v/v, with and without the addition of 0.1% (v/v formic acid were compared. Four different wheat organs were sampled, extracted and analysed by LC-HRMS. Data evaluation was performed with the in-house-developed MetExtract II software and R. With all tested solvents a total of 871 metabolites were extracted in ear, 785 in stem, 733 in leaf and 517 in root samples, respectively. Between 48% (stem and 57% (ear of the metabolites detected in a particular organ were found with all extraction mixtures, and 127 of 996 metabolites were consistently shared between all extraction agent/organ combinations. In aqueous methanol, acidification with formic acid led to pronounced pH dependency regarding the precision of metabolite abundance and the number of detectable metabolites, whereas extracts of acetonitrile-containing mixtures were less affected. Moreover, methanol and acetonitrile have been found to be complementary with respect to extraction efficiency. Interestingly, the beneficial properties of both solvents can be combined by the use of a water-methanol-acetonitrile mixture for global metabolite extraction instead of aqueous methanol or aqueous acetonitrile alone.

  7. Environmental Metabolomics of the Tomato Plant Surface Provides Insights on Salmonella enterica Colonization.

    Science.gov (United States)

    Han, Sanghyun; Micallef, Shirley A

    2016-05-15

    Foodborne illness-causing enteric bacteria are able to colonize plant surfaces without causing infection. We lack an understanding of how epiphytic persistence of enteric bacteria occurs on plants, possibly as an adaptive transit strategy to maximize chances of reentering herbivorous hosts. We used tomato (Solanum lycopersicum) cultivars that have exhibited differential susceptibilities to Salmonella enterica colonization to investigate the influence of plant surface compounds and exudates on enteric bacterial populations. Tomato fruit, shoot, and root exudates collected at different developmental stages supported growth of S. enterica to various degrees in a cultivar- and plant organ-dependent manner. S. enterica growth in fruit exudates of various cultivars correlated with epiphytic growth data (R(2) = 0.504; P = 0.006), providing evidence that plant surface compounds drive bacterial colonization success. Chemical profiling of tomato surface compounds with gas chromatography-time of flight mass spectrometry (GC-TOF-MS) provided valuable information about the metabolic environment on fruit, shoot, and root surfaces. Hierarchical cluster analysis of the data revealed quantitative differences in phytocompounds among cultivars and changes over a developmental course and by plant organ (P enterica growth, while fatty acids, including palmitic and oleic acids, were negatively correlated. We demonstrate that the plant surface metabolite landscape has a significant impact on S. enterica growth and colonization efficiency. This environmental metabolomics approach provides an avenue to understand interactions between human pathogens and plants that could lead to strategies to identify or breed crop cultivars for microbiologically safer produce. In recent years, fresh produce has emerged as a leading food vehicle for enteric pathogens. Salmonella-contaminated tomatoes represent a recurrent human pathogen-plant commodity pair. We demonstrate that Salmonella can utilize

  8. Metabolomics Based Profiling of Dexamethasone Side Effects in Rats

    Directory of Open Access Journals (Sweden)

    Abeer K. Malkawi

    2018-02-01

    Full Text Available 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.

  9. Metabolomic analysis of wild and transgenic Nicotiana langsdorffii plants exposed to abiotic stresses: unraveling metabolic responses.

    Science.gov (United States)

    Scalabrin, Elisa; Radaelli, Marta; Rizzato, Giovanni; Bogani, Patrizia; Buiatti, Marcello; Gambaro, Andrea; Capodaglio, Gabriele

    2015-08-01

    Nicotiana langsdorffii plants, wild and transgenic for the Agrobacterium rhizogenes rol C gene and the rat glucocorticoid receptor (GR) gene, were exposed to different abiotic stresses (high temperature, water deficit, and high chromium concentrations). An untargeted metabolomic analysis was carried out in order to investigate the metabolic effects of the inserted genes in response to the applied stresses and to obtain a comprehensive profiling of metabolites induced during abiotic stresses. High-performance liquid chromatography separation (HPLC) coupled to high-resolution mass spectrometry (HRMS) enabled the identification of more than 200 metabolites, and statistical analysis highlighted the most relevant compounds for each plant treatment. The plants exposed to heat stress showed a unique set of induced secondary metabolites, some of which were known while others were not previously reported for this kind of stress; significant changes were observed especially in lipid composition. The role of trichome, as a protection against heat stress, is here suggested by the induction of both acylsugars and glykoalkaloids. Water deficit and Cr(VI) stresses resulted mainly in enhanced antioxidant (HCAs, polyamine) levels and in the damage of lipids, probably as a consequence of reactive oxygen species (ROS) production. Moreover, the ability of rol C expression to prevent oxidative burst was confirmed. The results highlighted a clear influence of GR modification on plant stress response, especially to water deficiency-a phenomenon whose applications should be further investigated. This study provides new insights into the field of system biology and demonstrates the importance of metabolomics in the study of plant functioning. Graphical Abstract Untargeted metabolomic analysis was applied to wild type, GR and RolC modified Nicotiana Langsdorffii plants exposed to heat, water and Cr(VI) stresses. The key metabolites, highly affected by stress application, were identified

  10. Metabolomics and Epidemiology Working Group

    Science.gov (United States)

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

  11. Heavy metal tolerance in plants: Role of transcriptomics, proteomics, metabolomics and ionomics

    Directory of Open Access Journals (Sweden)

    Samiksha eSingh

    2016-02-01

    Full Text Available Heavy metal contamination of soil and water causing toxicity/stress has become one important constraint to crop productivity and quality. This situation has further worsened by the increasing population growth and inherent food demand. It have been reported in several studies that counterbalancing toxicity, due to heavy metal requires complex mechanisms at molecular, biochemical, physiological, cellular, tissue and whole plant level, which might manifest in terms of improved crop productivity. Recent advances in various disciplines of biological sciences such as metabolomics, transcriptomics, proteomics etc. have assisted in the characterization of metabolites, transcription factors, stress-inducible proteins involved in heavy metal tolerance, which in turn can be utilized for generating heavy metal tolerant crops. This review summarizes various tolerance strategies of plants under heavy metal toxicity, covering the role of metabolites (metabolomics, trace elements (ionomics, transcription factors (transcriptomics, various stress-inducible proteins (proteomics as well as the role of plant hormones. We also provide a glance at strategies adopted by metal accumulating plants also known as metallophytes.

  12. Heavy Metal Tolerance in Plants: Role of Transcriptomics, Proteomics, Metabolomics, and Ionomics.

    Science.gov (United States)

    Singh, Samiksha; Parihar, Parul; Singh, Rachana; Singh, Vijay P; Prasad, Sheo M

    2015-01-01

    Heavy metal contamination of soil and water causing toxicity/stress has become one important constraint to crop productivity and quality. This situation has further worsened by the increasing population growth and inherent food demand. It has been reported in several studies that counterbalancing toxicity due to heavy metal requires complex mechanisms at molecular, biochemical, physiological, cellular, tissue, and whole plant level, which might manifest in terms of improved crop productivity. Recent advances in various disciplines of biological sciences such as metabolomics, transcriptomics, proteomics, etc., have assisted in the characterization of metabolites, transcription factors, and stress-inducible proteins involved in heavy metal tolerance, which in turn can be utilized for generating heavy metal-tolerant crops. This review summarizes various tolerance strategies of plants under heavy metal toxicity covering the role of metabolites (metabolomics), trace elements (ionomics), transcription factors (transcriptomics), various stress-inducible proteins (proteomics) as well as the role of plant hormones. We also provide a glance of some strategies adopted by metal-accumulating plants, also known as "metallophytes."

  13. Heavy Metal Tolerance in Plants: Role of Transcriptomics, Proteomics, Metabolomics, and Ionomics

    Science.gov (United States)

    Singh, Samiksha; Parihar, Parul; Singh, Rachana; Singh, Vijay P.; Prasad, Sheo M.

    2016-01-01

    Heavy metal contamination of soil and water causing toxicity/stress has become one important constraint to crop productivity and quality. This situation has further worsened by the increasing population growth and inherent food demand. It has been reported in several studies that counterbalancing toxicity due to heavy metal requires complex mechanisms at molecular, biochemical, physiological, cellular, tissue, and whole plant level, which might manifest in terms of improved crop productivity. Recent advances in various disciplines of biological sciences such as metabolomics, transcriptomics, proteomics, etc., have assisted in the characterization of metabolites, transcription factors, and stress-inducible proteins involved in heavy metal tolerance, which in turn can be utilized for generating heavy metal-tolerant crops. This review summarizes various tolerance strategies of plants under heavy metal toxicity covering the role of metabolites (metabolomics), trace elements (ionomics), transcription factors (transcriptomics), various stress-inducible proteins (proteomics) as well as the role of plant hormones. We also provide a glance of some strategies adopted by metal-accumulating plants, also known as “metallophytes.” PMID:26904030

  14. Metabolomics and Cheminformatics Analysis of Antifungal Function of Plant Metabolites.

    Science.gov (United States)

    Cuperlovic-Culf, Miroslava; Rajagopalan, NandhaKishore; Tulpan, Dan; Loewen, Michele C

    2016-09-30

    Fusarium head blight (FHB), primarily caused by Fusarium graminearum , is a devastating disease of wheat. Partial resistance to FHB of several wheat cultivars includes specific metabolic responses to inoculation. Previously published studies have determined major metabolic changes induced by pathogens in resistant and susceptible plants. Functionality of the majority of these metabolites in resistance remains unknown. In this work we have made a compilation of all metabolites determined as selectively accumulated following FHB inoculation in resistant plants. Characteristics, as well as possible functions and targets of these metabolites, are investigated using cheminformatics approaches with focus on the likelihood of these metabolites acting as drug-like molecules against fungal pathogens. Results of computational analyses of binding properties of several representative metabolites to homology models of fungal proteins are presented. Theoretical analysis highlights the possibility for strong inhibitory activity of several metabolites against some major proteins in Fusarium graminearum , such as carbonic anhydrases and cytochrome P450s. Activity of several of these compounds has been experimentally confirmed in fungal growth inhibition assays. Analysis of anti-fungal properties of plant metabolites can lead to the development of more resistant wheat varieties while showing novel application of cheminformatics approaches in the analysis of plant/pathogen interactions.

  15. Metabolomics and Cheminformatics Analysis of Antifungal Function of Plant Metabolites

    Directory of Open Access Journals (Sweden)

    Miroslava Cuperlovic-Culf

    2016-09-01

    Full Text Available Fusarium head blight (FHB, primarily caused by Fusarium graminearum, is a devastating disease of wheat. Partial resistance to FHB of several wheat cultivars includes specific metabolic responses to inoculation. Previously published studies have determined major metabolic changes induced by pathogens in resistant and susceptible plants. Functionality of the majority of these metabolites in resistance remains unknown. In this work we have made a compilation of all metabolites determined as selectively accumulated following FHB inoculation in resistant plants. Characteristics, as well as possible functions and targets of these metabolites, are investigated using cheminformatics approaches with focus on the likelihood of these metabolites acting as drug-like molecules against fungal pathogens. Results of computational analyses of binding properties of several representative metabolites to homology models of fungal proteins are presented. Theoretical analysis highlights the possibility for strong inhibitory activity of several metabolites against some major proteins in Fusarium graminearum, such as carbonic anhydrases and cytochrome P450s. Activity of several of these compounds has been experimentally confirmed in fungal growth inhibition assays. Analysis of anti-fungal properties of plant metabolites can lead to the development of more resistant wheat varieties while showing novel application of cheminformatics approaches in the analysis of plant/pathogen interactions.

  16. Cardioprotective and Metabolomic Profiling of Selected Medicinal Plants against Oxidative Stress

    Directory of Open Access Journals (Sweden)

    Nadia Afsheen

    2018-01-01

    Full Text Available In this research work, the antioxidant and metabolomic profiling of seven selected medicinally important herbs including Rauvolfia serpentina, Terminalia arjuna, Coriandrum sativum, Elettaria cardamom, Piper nigrum, Allium sativum, and Crataegus oxyacantha was performed. The in vivo cardioprotective potential of these medicinal plants was evaluated against surgically induced oxidative stress through left anterior descending coronary artery ligation (LADCA in dogs. The antioxidant profiling of these plants was done through DPPH and DNA protection assay. The C. oxyacantha and T. arjuna showed maximum antioxidant potential, while the E. cardamom showed poor antioxidative strength even at its high concentration. Different concentrations of extracts of the said plants exhibited the protection of plasmid DNA against H2O2 damage as compared to the plasmid DNA merely treated with H2O2. The metabolomic profiling through LC-MS analysis of these antioxidants revealed the presence of active secondary metabolites responsible for their antioxidant potential. During in vivo analysis, blood samples of all treatment groups were drawn at different time intervals to analyze the cardiac and hemodynamic parameters. The results depicted that the group pretreated with HC4 significantly sustained the level of CK-MB, SGOT, and LDH as well as hemodynamic parameters near to normal. The histopathological examination also confirmed the cardioprotective potential of HC4. Thus, the HC4 being safe and inexpensive cardioprotective herbal combination could be considered as an alternate of synthetic drugs.

  17. Plant stress biomarkers from biosimulations: the Transcriptome-To-Metabolome (TTM) technology - effects of drought stress on rice.

    Science.gov (United States)

    Phelix, C F; Feltus, F A

    2015-01-01

    Measuring biomarkers from plant tissue samples is challenging and expensive when the desire is to integrate transcriptomics, fluxomics, metabolomics, lipidomics, proteomics, physiomics and phenomics. We present a computational biology method where only the transcriptome needs to be measured and is used to derive a set of parameters for deterministic kinetic models of metabolic pathways. The technology is called Transcriptome-To-Metabolome (TTM) biosimulations, currently under commercial development, but available for non-commercial use by researchers. The simulated results on metabolites of 30 primary and secondary metabolic pathways in rice (Oryza sativa) were used as the biomarkers to predict whether the transcriptome was from a plant that had been under drought conditions. The rice transcriptomes were accessed from public archives and each individual plant was simulated. This unique quality of the TTM technology allows standard analyses on biomarker assessments, i.e. sensitivity, specificity, positive and negative predictive values, accuracy, receiver operator characteristics (ROC) curve and area under the ROC curve (AUC). Two validation methods were also used, the holdout and 10-fold cross validations. Initially 17 metabolites were identified as candidate biomarkers based on either statistical significance on binary phenotype when compared with control samples or recognition from the literature. The top three biomarkers based on AUC were gibberellic acid 12 (0.89), trehalose (0.80) and sn1-palmitate-sn2-oleic-phosphatidylglycerol (0.70). Neither heat map analyses of transcriptomes nor all 300 metabolites clustered the stressed and control groups effectively. The TTM technology allows the emergent properties of the integrated system to generate unique and useful 'Omics' information. © 2014 German Botanical Society and The Royal Botanical Society of the Netherlands.

  18. New frontiers in pharmaceutical analysis: A metabolomic approach to check batch compliance of complex products based on natural substances.

    Science.gov (United States)

    Mattoli, L; Burico, M; Fodaroni, G; Tamimi, S; Bedont, S; Traldi, P; Stocchero, M

    2016-07-15

    Natural substances, particularly medicinal plants and their extracts, are still today intended as source for new Active Pharmaceutical Ingredients (APIs). Alternatively they can be validly employed to prepare medicines, food supplements or medical devices. The most adopted analytical approach used to verify quality of natural substances like medicinal plants is based still today on the traditional quantitative determination of marker compounds and/or active ingredients, besides the acquisition of a fingerprint by TLC, NIR, HPLC, GC. Here a new analytical approach based on untargeted metabolomic fingerprinting by means of Mass Spectrometry (MS) to verify the quality of grinTuss adulti syrup, a complex products based on medicinal plants, is proposed. Recently, untargeted metabolomic has been successfully applied to assess quality of natural substances, plant extracts, as well as corresponding formulated products, being the complexity a resource but not necessarily a limit. The untargeted metabolomic fingerprinting includes the monitoring of the main constituents, giving weighted relevance to the most abundant ones, but also considering minor components, that might be notable in view of an integrated - often synergistic - effect on the biological system. Two different years of production were investigated. The collected samples were analyzed by Flow Injection ElectroSpray Ionization Mass Spectrometry Analysis (FIA-ESI-MS) and a suitable data processing procedure was developed to transform the MS spectra into robust fingerprints. Multivariate Statistical Process Control (MSPC) was applied in order to obtain multivariate control charts that were validated to prove the effectiveness of the proposed method. Copyright © 2016 The Authors. Published by Elsevier B.V. All rights reserved.

  19. Metabolic Effect of Dietary Taurine Supplementation on Nile Tilapia (Oreochromis nilotictus) Evaluated by NMR-Based Metabolomics.

    Science.gov (United States)

    Shen, Guiping; Huang, Ying; Dong, Jiyang; Wang, Xuexi; Cheng, Kian-Kai; Feng, Jianghua; Xu, Jingjing; Ye, Jidan

    2018-01-10

    Taurine is indispensable in aquatic diets that are based solely on plant protein, and it promotes growth of many fish species. However, the physiological and metabolome effects of taurine on fish have not been well described. In this study, 1 H NMR-based metabolomics approaches were applied to investigate the metabolite variations in Nile tilapia (Oreochromis nilotictus) muscle in order to visualize the metabolic trajectory and reveal the possible mechanisms of metabolic effects of dietary taurine supplementation on tilapia growth. After extraction using aqueous and organic solvents, 19 taurine-induced metabolic changes were evaluated in our study. The metabolic changes were characterized by differences in carbohydrate, amino acid, lipid, and nucleotide contents. The results indicate that taurine supplementation could significantly regulate the physiological state of fish and promote growth and development. These results provide a basis for understanding the mechanism of dietary taurine supplementation in fish feeding. 1 H NMR spectroscopy, coupled with multivariate pattern recognition technologies, is an efficient and useful tool to map the fish metabolome and identify metabolic responses to different dietary nutrients in aquaculture.

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

    Directory of Open Access Journals (Sweden)

    Juan I. Vílchez

    2018-02-01

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

  1. Genetic algorithm based two-mode clustering of metabolomics data

    NARCIS (Netherlands)

    Hageman, J.A.; van den Berg, R.A.; Westerhuis, J.A.; van der Werf, M.J.; Smilde, A.K.

    2008-01-01

    Metabolomics and other omics tools are generally characterized by large data sets with many variables obtained under different environmental conditions. Clustering methods and more specifically two-mode clustering methods are excellent tools for analyzing this type of data. Two-mode clustering

  2. Illuminating a plant's tissue-specific metabolic diversity using computational metabolomics and information theory.

    Science.gov (United States)

    Li, Dapeng; Heiling, Sven; Baldwin, Ian T; Gaquerel, Emmanuel

    2016-11-22

    Secondary metabolite diversity is considered an important fitness determinant for plants' biotic and abiotic interactions in nature. This diversity can be examined in two dimensions. The first one considers metabolite diversity across plant species. A second way of looking at this diversity is by considering the tissue-specific localization of pathways underlying secondary metabolism within a plant. Although these cross-tissue metabolite variations are increasingly regarded as important readouts of tissue-level gene function and regulatory processes, they have rarely been comprehensively explored by nontargeted metabolomics. As such, important questions have remained superficially addressed. For instance, which tissues exhibit prevalent signatures of metabolic specialization? Reciprocally, which metabolites contribute most to this tissue specialization in contrast to those metabolites exhibiting housekeeping characteristics? Here, we explore tissue-level metabolic specialization in Nicotiana attenuata, an ecological model with rich secondary metabolism, by combining tissue-wide nontargeted mass spectral data acquisition, information theory analysis, and tandem MS (MS/MS) molecular networks. This analysis was conducted for two different methanolic extracts of 14 tissues and deconvoluted 895 nonredundant MS/MS spectra. Using information theory analysis, anthers were found to harbor the most specialized metabolome, and most unique metabolites of anthers and other tissues were annotated through MS/MS molecular networks. Tissue-metabolite association maps were used to predict tissue-specific gene functions. Predictions for the function of two UDP-glycosyltransferases in flavonoid metabolism were confirmed by virus-induced gene silencing. The present workflow allows biologists to amortize the vast amount of data produced by modern MS instrumentation in their quest to understand gene function.

  3. HPLC-based metabolomics to identify cytotoxic compounds from Plectranthus amboinicus (Lour.) Spreng against human breast cancer MCF-7Cells.

    Science.gov (United States)

    Yulianto, Wahid; Andarwulan, Nuri; Giriwono, Puspo Edi; Pamungkas, Joko

    2016-12-15

    The objective of this study was to identify the active compounds in Plectranthus amboinicus (Lour.) Spreng which play a role to inhibit viability of breast cancer MCF-7 cells using HPLC-based metabolomics approach. Five fractions of the plant extract were observed including ethanol, hexane, chloroform, ethyl acetate and water fraction. There were 45 HPLC chromatograms resulted from 5 fractions with 3 replications and 3 wavelengths detection. The chromatograms were compared to the data of IC 50 from MTT assay of each fraction against human breast cancer MCF-7 cells using metabolomics. The OPLS analysis result promptly pointed towards a chloroform fraction at retention time of 40.16-41.28min that has the greatest contribution to the cytotoxic activity. The data of mass spectra indicated that an abietane diterpene namely 7-acetoxy-6-hydroxyroyleanone was the main compound that contributed to the cytotoxic activity. This metabolomics application method can be used as a quick preliminary guideline to uncover the most dominant compound related to the bioactivity. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis.

    Science.gov (United States)

    Huang, Sijia; Chong, Nicole; Lewis, Nathan E; Jia, Wei; Xie, Guoxiang; Garmire, Lana X

    2016-03-31

    More accurate diagnostic methods are pressingly needed to diagnose breast cancer, the most common malignant cancer in women worldwide. Blood-based metabolomics is a promising diagnostic method for breast cancer. However, many metabolic biomarkers are difficult to replicate among studies. We propose that higher-order functional representation of metabolomics data, such as pathway-based metabolomic features, can be used as robust biomarkers for breast cancer. Towards this, we have developed a new computational method that uses personalized pathway dysregulation scores for disease diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods. The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under the Curve, a receiver operating characteristic curve) of 0.968 and 0.934, sensitivities of 0.946 and 0.954, and specificities of 0.934 and 0.918. These two metabolomics-based pathway models are further validated by RNA-Seq-based TCGA (The Cancer Genome Atlas) breast cancer data, with AUCs of 0.995 and 0.993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer. We have successfully developed a new type of pathway-based model to study metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease diagnosis.

  5. NMR-based metabolomics of mammalian cell and tissue cultures

    International Nuclear Information System (INIS)

    Aranibar, Nelly; Borys, Michael; Mackin, Nancy A.; Ly, Van; Abu-Absi, Nicholas; Abu-Absi, Susan; Niemitz, Matthias; Schilling, Bernhard; Li, Zheng Jian; Brock, Barry; Russell, Reb J.; Tymiak, Adrienne; Reily, Michael D.

    2011-01-01

    NMR spectroscopy was used to evaluate growth media and the cellular metabolome in two systems of interest to biomedical research. The first of these was a Chinese hamster ovary cell line engineered to express a recombinant protein. Here, NMR spectroscopy and a quantum mechanical total line shape analysis were utilized to quantify 30 metabolites such as amino acids, Krebs cycle intermediates, activated sugars, cofactors, and others in both media and cell extracts. The impact of bioreactor scale and addition of anti-apoptotic agents to the media on the extracellular and intracellular metabolome indicated changes in metabolic pathways of energy utilization. These results shed light into culture parameters that can be manipulated to optimize growth and protein production. Second, metabolomic analysis was performed on the superfusion media in a common model used for drug metabolism and toxicology studies, in vitro liver slices. In this study, it is demonstrated that two of the 48 standard media components, choline and histidine are depleted at a faster rate than many other nutrients. Augmenting the starting media with extra choline and histidine improves the long-term liver slice viability as measured by higher tissues levels of lactate dehydrogenase (LDH), glutathione and ATP, as well as lower LDH levels in the media at time points out to 94 h after initiation of incubation. In both models, media components and cellular metabolites are measured over time and correlated with currently accepted endpoint measures.

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

    Science.gov (United States)

    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.

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

    Directory of Open Access Journals (Sweden)

    Carroll Adam J

    2010-07-01

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

  8. LC-MS-Based Metabolomic Investigation of Chemopreventive Phytochemical-Elicited Metabolic Events.

    Science.gov (United States)

    Wang, Lei; Yao, Dan; Chen, Chi

    2016-01-01

    Phytochemicals are under intensive investigation for their potential use as chemopreventive agents in blocking or suppressing carcinogenesis. Metabolic interactions between phytochemical and biological system play an important role in determining the efficacy and toxicity of chemopreventive phytochemicals. However, complexities of phytochemical biotransformation and intermediary metabolism pose challenges for studying phytochemical-elicited metabolic events. Metabolomics has become a highly effective technical platform to detect subtle changes in a complex metabolic system. Here, using green tea polyphenols as an example, we describe a workflow of LC-MS-based metabolomics study, covering the procedures and techniques in sample collection, preparation, LC-MS analysis, data analysis, and interpretation.

  9. Study of Leaf Metabolome Modifications Induced by UV-C Radiations in Representative Vitis, Cissus and Cannabis Species by LC-MS Based Metabolomics and Antioxidant Assays

    Directory of Open Access Journals (Sweden)

    Guillaume Marti

    2014-09-01

    Full Text Available UV-C radiation is known to induce metabolic modifications in plants, particularly to secondary metabolite biosynthesis. To assess these modifications from a global and untargeted perspective, the effects of the UV-C radiation of the leaves of three different model plant species, Cissus antarctica Vent. (Vitaceae, Vitis vinifera L. (Vitaceae and Cannabis sativa L. (Cannabaceae, were evaluated by an LC-HRMS-based metabolomic approach. The approach enabled the detection of significant metabolite modifications in the three species studied. For all species, clear modifications of phenylpropanoid metabolism were detected that led to an increased level of stilbene derivatives. Interestingly, resveratrol and piceid levels were strongly induced by the UV-C treatment of C. antarctica leaves. In contrast, both flavonoids and stilbene polymers were upregulated in UV-C-treated Vitis leaves. In Cannabis, important changes in cinnamic acid amides and stilbene-related compounds were also detected. Overall, our results highlighted phytoalexin induction upon UV-C radiation. To evaluate whether UV-C stress radiation could enhance the biosynthesis of bioactive compounds, the antioxidant activity of extracts from control and UV-C-treated leaves was measured. The results showed increased antioxidant activity in UV-C-treated V. vinifera extracts.

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

    Science.gov (United States)

    Rácz, Anita; Andrić, Filip; Bajusz, Dávid; Héberger, Károly

    2018-01-01

    Contemporary metabolomic fingerprinting is based on multiple spectrometric and chromatographic signals, used either alone or combined with structural and chemical information of metabolic markers at the qualitative and semiquantitative level. However, signal shifting, convolution, and matrix effects may compromise metabolomic patterns. Recent increase in the use of qualitative metabolomic data, described by the presence (1) or absence (0) of particular metabolites, demonstrates great potential in the field of metabolomic profiling and fingerprint analysis. The aim of this study is a comprehensive evaluation of binary similarity measures for the elucidation of patterns among samples of different botanical origin and various metabolomic profiles. Nine qualitative metabolomic data sets covering a wide range of natural products and metabolomic profiles were applied to assess 44 binary similarity measures for the fingerprinting of plant extracts and natural products. The measures were analyzed by the novel sum of ranking differences method (SRD), searching for the most promising candidates. Baroni-Urbani-Buser (BUB) and Hawkins-Dotson (HD) similarity coefficients were selected as the best measures by SRD and analysis of variance (ANOVA), while Dice (Di1), Yule, Russel-Rao, and Consonni-Todeschini 3 ranked the worst. ANOVA revealed that concordantly and intermediately symmetric similarity coefficients are better candidates for metabolomic fingerprinting than the asymmetric and correlation based ones. The fingerprint analysis based on the BUB and HD coefficients and qualitative metabolomic data performed equally well as the quantitative metabolomic profile analysis. Fingerprint analysis based on the qualitative metabolomic profiles and binary similarity measures proved to be a reliable way in finding the same/similar patterns in metabolomic data as that extracted from quantitative data.

  11. Mass spectrometry-based metabolomics of single yeast cells.

    Science.gov (United States)

    Ibáñez, Alfredo J; Fagerer, Stephan R; Schmidt, Anna Mareike; Urban, Pawel L; Jefimovs, Konstantins; Geiger, Philipp; Dechant, Reinhard; Heinemann, Matthias; Zenobi, Renato

    2013-05-28

    Single-cell level measurements are necessary to characterize the intrinsic biological variability in a population of cells. In this study, we demonstrate that, with the microarrays for mass spectrometry platform, we are able to observe this variability. We monitor environmentally (2-deoxy-D-glucose) and genetically (ΔPFK2) perturbed Saccharomyces cerevisiae cells at the single-cell, few-cell, and population levels. Correlation plots between metabolites from the glycolytic pathway, as well as with the observed ATP/ADP ratio as a measure of cellular energy charge, give biological insight that is not accessible from population-level metabolomic data.

  12. Accurate mass error correction in liquid chromatography time-of-flight mass spectrometry based metabolomics

    NARCIS (Netherlands)

    Mihaleva, V.V.; Vorst, O.F.J.; Maliepaard, C.A.; Verhoeven, H.A.; Vos, de C.H.; Hall, R.D.; Ham, van R.C.H.J.

    2008-01-01

    Compound identification and annotation in (untargeted) metabolomics experiments based on accurate mass require the highest possible accuracy of the mass determination. Experimental LC/TOF-MS platforms equipped with a time-to-digital converter (TDC) give the best mass estimate for those mass signals

  13. Integration of metabolomics and proteomics in molecular plant physiology--coping with the complexity by data-dimensionality reduction.

    Science.gov (United States)

    Weckwerth, Wolfram

    2008-02-01

    In recent years, genomics has been extended to functional genomics. Toward the characterization of organisms or species on the genome level, changes on the metabolite and protein level have been shown to be essential to assign functions to genes and to describe the dynamic molecular phenotype. Gas chromatography (GC) and liquid chromatography coupled to mass spectrometry (GC- and LC-MS) are well suited for the fast and comprehensive analysis of ultracomplex metabolite samples. For the integration of metabolite profiles with quantitative protein profiles, a high throughput (HTP) shotgun proteomics approach using LC-MS and label-free quantification of unique proteins in a complex protein digest is described. Multivariate statistics are applied to examine sample pattern recognition based on data-dimensionality reduction and biomarker identification in plant systems biology. The integration of the data reveal multiple correlative biomarkers providing evidence for an increase of information in such holistic approaches. With computational simulation of metabolic networks and experimental measurements, it can be shown that biochemical regulation is reflected by metabolite network dynamics measured in a metabolomics approach. Examples in molecular plant physiology are presented to substantiate the integrative approach.

  14. Quantitative metabolomics based on gas chromatography mass spectrometry: Status and perspectives

    NARCIS (Netherlands)

    Koek, M.M.; Jellema, R.H.; Greef, J. van der; Tas, A.C.; Hankemeier, T.

    2011-01-01

    Metabolomics involves the unbiased quantitative and qualitative analysis of the complete set of metabolites present in cells, body fluids and tissues (the metabolome). By analyzing differences between metabolomes using biostatistics (multivariate data analysis; pattern recognition), metabolites

  15. Waste materials derived bio-effectors used as growth promoters for strawberry plants. An agronomic and metabolomic study

    Science.gov (United States)

    Vasileva, Brankica; Chami, Ziad Al; De Pascali, Sandra; Cavoski, Ivana; Fanizzi, Francesco Paolo

    2015-04-01

    Recently, a novel concept of bio-effectors has emerged to describe a group of products that are able to improve plant performance more than fertilizers. In this study, three different agro-industrial residues, i.e. brewers' spent grain (BSG), fennel processing residues (FPR) and lemon processing residues (LPR) were chosen as potential bio-effectors. A greenhouse soilless pot experiment was conducted on strawberry plants (Fragaria x ananassa var. Festival) in order to study the effect of BSG, FPR and LPR water extracts, at different concentrations, on plant growth and fruit quality. Their effect was compared with humic-like substances as a positive/reference control (Ctrl+) and with Hoagland solution as a negative control (Ctrl-). Agronomic parameters and the nutrient uptake were measured on shoots, roots and fruits. Metabolomic profiling tests were carried out on leaves, roots and fruit juices through the NMR technique. Plants treated with the FPR extract showed better vegetative growth, while plants treated with the BSG extract gave higher yield and better fruit size. Metabolomic profiling showed that fruits and roots of plants treated with FPR and LPR extracts had higher concentrations of sucrose, malate and acetate, while BSG treated plants had higher concentrations of citrate and β-glucose. In conclusion, according to the results achieved, the bio-effectors used in this study promote plant growth and fruit quality regardless of their nutritional content. Keywords: bio-effectors, agro-industrial waste, nuclear magnetic resonance (NMR), strawberry, growth promotion, fruit quality.

  16. Metabolic changes associated with papillary thyroid carcinoma: A nuclear magnetic resonance-based metabolomics study.

    Science.gov (United States)

    Li, Yanyun; Chen, Minjian; Liu, Cuiping; Xia, Yankai; Xu, Bo; Hu, Yanhui; Chen, Ting; Shen, Meiping; Tang, Wei

    2018-05-01

    Papillary thyroid carcinoma (PTC) is the most common thyroid cancer. Nuclear magnetic resonance (NMR)‑based metabolomic technique is the gold standard in metabolite structural elucidation, and can provide different coverage of information compared with other metabolomic techniques. Here, we firstly conducted NMR based metabolomics study regarding detailed metabolic changes especially metabolic pathway changes related to PTC pathogenesis. 1H NMR-based metabolomic technique was adopted in conju-nction with multivariate analysis to analyze matched tumor and normal thyroid tissues obtained from 16 patients. The results were further annotated with Kyoto Encyclopedia of Genes and Genomes (KEGG), and Human Metabolome Database, and then were analyzed using modules of pathway analysis and enrichment analysis of MetaboAnalyst 3.0. Based on the analytical techniques, we established the models of principal component analysis (PCA), partial least squares-discriminant analysis (PLS-DA), and orthogonal partial least-squares discriminant analysis (OPLS‑DA) which could discriminate PTC from normal thyroid tissue, and found 15 robust differentiated metabolites from two OPLS-DA models. We identified 8 KEGG pathways and 3 pathways of small molecular pathway database which were significantly related to PTC by using pathway analysis and enrichment analysis, respectively, through which we identified metabolisms related to PTC including branched chain amino acid metabolism (leucine and valine), other amino acid metabolism (glycine and taurine), glycolysis (lactate), tricarboxylic acid cycle (citrate), choline metabolism (choline, ethanolamine and glycerolphosphocholine) and lipid metabolism (very-low‑density lipoprotein and low-density lipoprotein). In conclusion, the PTC was characterized with increased glycolysis and inhibited tricarboxylic acid cycle, increased oncogenic amino acids as well as abnormal choline and lipid metabolism. The findings in this study provide new

  17. Discovery of biomarkers for oxidative stress based on cellular metabolomics.

    Science.gov (United States)

    Wang, Ningli; Wei, Jianteng; Liu, Yewei; Pei, Dong; Hu, Qingping; Wang, Yu; Di, Duolong

    2016-07-01

    Oxidative stress has a close relationship with various pathologic physiology phenomena and the potential biomarkers of oxidative stress may provide evidence for clinical diagnosis or disease prevention. Metabolomics was employed to identify the potential biomarkers of oxidative stress. High-performance liquid chromatography-diode array detector, mass spectrometry and partial least squares discriminate analysis were used in this study. The 10, 15 and 13 metabolites were considered to discriminate the model group, vitamin E-treated group and l-glutathione-treated group, respectively. Some of them have been identified, namely, malic acid, vitamin C, reduced glutathione and tryptophan. Identification of other potential biomarkers should be conducted and their physiological significance also needs to be elaborated.

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

    KAUST Repository

    Emwas, Abdul-Hamid M.

    2013-04-03

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

  19. Metabolomics-Based Screening of Biofilm-Inhibitory Compounds against Pseudomonas aeruginosa from Burdock Leaf

    Directory of Open Access Journals (Sweden)

    Zaixiang Lou

    2015-09-01

    Full Text Available Screening of anti-biofilm compounds from the burdock leaf based on metabolomics is reported here. The crystal violet assay indicated 34% ethanol elution fraction of burdock leaf could completely inhibit biofilm formation of Pseudomonas aeruginosa at 1 mg·mL−1. Then, the chemical composition of burdock leaf fraction was analyzed by ultra-performance liquid chromatography-mass spectrometry (UPLC-MS and 11 active compounds (chlorogenic acid, caffeic acid, p-coumaric acid, quercetin, ursolic acid, rutin, cynarin, luteolin, crocin, benzoic acid, and Tenacissoside I were identified. Lastly, UPLC-MS analysis was employed to obtain the metabolic fingerprints of burdock leaf fractions before and after inhibiting the biofilm of Pseudomonas aeruginosa. The metabolic fingerprints were transformed to data, analyzed with PLS-DA (partial least squares discriminant analysis and the peaks whose area was significantly changed were found out. Thus, 81 compounds were screened as potential anti-biofilm ingredients. Among them, rutin, ursolic acid, caffeic acid, p-coumaric acid and quercetin were identified and confirmed as the main anti-biofilm compounds in burdock leaf. The study provided basic anti-biofilm profile data for the compounds in burdock leaf, as well as provided a convenient method for fast screening of anti-biofilm compounds from natural plants.

  20. Metabolomics as a Tool to Investigate Abiotic Stress Tolerance in Plants

    Directory of Open Access Journals (Sweden)

    Aurelio Gómez-Cadenas

    2013-03-01

    Full Text Available Metabolites reflect the integration of gene expression, protein interaction and other different regulatory processes and are therefore closer to the phenotype than mRNA transcripts or proteins alone. Amongst all –omics technologies, metabolomics is the most transversal and can be applied to different organisms with little or no modifications. It has been successfully applied to the study of molecular phenotypes of plants in response to abiotic stress in order to find particular patterns associated to stress tolerance. These studies have highlighted the essential involvement of primary metabolites: sugars, amino acids and Krebs cycle intermediates as direct markers of photosynthetic dysfunction as well as effectors of osmotic readjustment. On the contrary, secondary metabolites are more specific of genera and species and respond to particular stress conditions as antioxidants, Reactive Oxygen Species (ROS scavengers, coenzymes, UV and excess radiation screen and also as regulatory molecules. In addition, the induction of secondary metabolites by several abiotic stress conditions could also be an effective mechanism of cross-protection against biotic threats, providing a link between abiotic and biotic stress responses. Moreover, the presence/absence and relative accumulation of certain metabolites along with gene expression data provides accurate markers (mQTL or MWAS for tolerant crop selection in breeding programs.

  1. Nutri-metabolomics: subtle serum metabolic differences in healthy subjects by NMR-based metabolomics after a short-term nutritional intervention with two tomato sauces.

    Science.gov (United States)

    Bondia-Pons, Isabel; Cañellas, Nicolau; Abete, Itziar; Rodríguez, Miguel Ángel; Perez-Cornago, Aurora; Navas-Carretero, Santiago; Zulet, M Ángeles; Correig, Xavier; Martínez, J Alfredo

    2013-12-01

    Postgenomics research and development is witnessing novel intersections of omics data intensive technology and applications in health and personalized nutrition. Chief among these is the nascent field of nutri-metabolomics that harnesses metabolomics platforms to discern person-to-person variations in nutritional responses. To this end, differences in the origin and ripening stage of fruits might have a strong impact on their phytochemical composition, and consequently, on their potential nutri-metabolomics effects on health. The objective of the present study was to evaluate the effects of a 4-week cross-over nutritional intervention on the metabolic status of 24 young healthy subjects. The intervention was carried out with two tomato sauces differing in their natural lycopene content, which was achieved by using tomatoes harvested at different times. Blood samples were drawn from each subject before and after each intervention period. Aqueous and lipid extracts from serum samples were analyzed by 1H-NMR metabolic profiling combined with analysis of variance simultaneous component analysis (ASCA) and multilevel simultaneous component analysis (MSCA). These methods allowed the interpretation of the variation induced by the main factors of the study design (sauce treatment and time). The levels of creatine, creatinine, leucine, choline, methionine, and acetate in aqueous extracts were increased after the intervention with the high-lycopene content sauce, while those of ascorbic acid, lactate, pyruvate, isoleucine, alanine were increased after the normal-lycopene content sauce. In conclusion, NMR-based metabolomics of aqueous and lipid extracts allowed the detection of different metabolic changes after the nutritional intervention. This outcome might partly be due to the different ripening state of the fruits used in production of the tomato sauces. The findings presented herein collectively attest to the emergence of the field of nutri-metabolomics as a novel

  2. MET-XAlign: a metabolite cross-alignment tool for LC/MS-based comparative metabolomics.

    Science.gov (United States)

    Zhang, Wenchao; Lei, Zhentian; Huhman, David; Sumner, Lloyd W; Zhao, Patrick X

    2015-09-15

    Liquid chromatography/mass spectrometry (LC/MS) metabolite profiling has been widely used in comparative metabolomics studies; however, LC/MS-based comparative metabolomics currently faces several critical challenges. One of the greatest challenges is how to effectively align metabolites across different LC/MS profiles; a single metabolite can give rise to multiple peak features, and the grouped peak features that can be used to construct a spectrum pattern of single metabolite can vary greatly between biochemical experiments and even between instrument runs. Another major challenge is that the observed retention time for a single metabolite can also be significantly affected by experimental conditions. To overcome these two key challenges, we present a novel metabolite-based alignment approach entitled MET-XAlign to align metabolites across LC/MS metabolomics profiles. MET-XAlign takes the deduced molecular mass and estimated compound retention time information that can be extracted by our previously published tool, MET-COFEA, and aligns metabolites based on this information. We demonstrate that MET-XAlign is able to cross-align metabolite compounds, either known or unknown, in LC/MS profiles not only across different samples but also across different biological experiments and different electrospray ionization modes. Therefore, our proposed metabolite-based cross-alignment approach is a great step forward and its implementation, MET-XAlign, is a very useful tool in LC/MS-based comparative metabolomics. MET-XAlign has been successfully implemented with core algorithm coding in C++, making it very efficient, and visualization interface coding in the Microsoft.NET Framework. The MET-XAlign software along with demonstrative data is freely available at http://bioinfo.noble.org/manuscript-support/met-xalign/ .

  3. Novel personalized pathway-based metabolomics models reveal key metabolic pathways for breast cancer diagnosis

    DEFF Research Database (Denmark)

    Huang, Sijia; Chong, Nicole; Lewis, Nathan

    2016-01-01

    diagnosis. We applied this method to predict breast cancer occurrence, in combination with correlation feature selection (CFS) and classification methods. Results: The resulting all-stage and early-stage diagnosis models are highly accurate in two sets of testing blood samples, with average AUCs (Area Under.......993. Moreover, important metabolic pathways, such as taurine and hypotaurine metabolism and the alanine, aspartate, and glutamate pathway, are revealed as critical biological pathways for early diagnosis of breast cancer. Conclusions: We have successfully developed a new type of pathway-based model to study...... metabolomics data for disease diagnosis. Applying this method to blood-based breast cancer metabolomics data, we have discovered crucial metabolic pathway signatures for breast cancer diagnosis, especially early diagnosis. Further, this modeling approach may be generalized to other omics data types for disease...

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

    Science.gov (United States)

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

    2016-08-01

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

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

    OpenAIRE

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

    2012-01-01

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

  6. Metabolomics based predictive biomarker model of ARDS: A systemic measure of clinical hypoxemia.

    Directory of Open Access Journals (Sweden)

    Neeraj Sinha

    Full Text Available Despite advancements in ventilator technologies, lung supportive and rescue therapies, the outcome and prognostication in acute respiratory distress syndrome (ARDS remains incremental and ambiguous. Metabolomics is a potential insightful measure to the diagnostic approaches practiced in critical disease settings. In our study patients diagnosed with mild and moderate/severe ARDS clinically governed by hypoxemic P/F ratio between 100-300 but with indistinct molecular phenotype were discriminated employing nuclear magnetic resonance (NMR based metabolomics of mini bronchoalveolar lavage fluid (mBALF. Resulting biomarker prototype comprising six metabolites was substantiated highlighting ARDS susceptibility/recovery. Both the groups (mild and moderate/severe ARDS showed distinct biochemical profile based on 83.3% classification by discriminant function analysis and cross validated accuracy of 91% using partial least squares discriminant analysis as major classifier. The predictive performance of narrowed down six metabolites were found analogous with chemometrics. The proposed biomarker model consisting of six metabolites proline, lysine/arginine, taurine, threonine and glutamate were found characteristic of ARDS sub-stages with aberrant metabolism observed mainly in arginine, proline metabolism, lysine synthesis and so forth correlating to diseased metabotype. Thus NMR based metabolomics has provided new insight into ARDS sub-stages and conclusively a precise biomarker model proposed, reflecting underlying metabolic dysfunction aiding prior clinical decision making.

  7. Cultivar Diversity of Grape Skin Polyphenol Composition and Changes in Response to Drought Investigated by LC-MS Based Metabolomics

    Directory of Open Access Journals (Sweden)

    Lucie Pinasseau

    2017-10-01

    Full Text Available Phenolic compounds represent a large family of plant secondary metabolites, essential for the quality of grape and wine and playing a major role in plant defense against biotic and abiotic stresses. Phenolic composition is genetically driven and greatly affected by environmental factors, including water stress. A major challenge for breeding of grapevine cultivars adapted to climate change and with high potential for wine-making is to dissect the complex plant metabolic response involved in adaptation mechanisms. A targeted metabolomics approach based on ultra high-performance liquid chromatography coupled to triple quadrupole mass spectrometry (UHPLC-QqQ-MS analysis in the Multiple Reaction Monitoring (MRM mode has been developed for high throughput profiling of the phenolic composition of grape skins. This method enables rapid, selective, and sensitive quantification of 96 phenolic compounds (anthocyanins, phenolic acids, stilbenoids, flavonols, dihydroflavonols, flavan-3-ol monomers, and oligomers…, and of the constitutive units of proanthocyanidins (i.e., condensed tannins, giving access to detailed polyphenol composition. It was applied on the skins of mature grape berries from a core-collection of 279 Vitis vinifera cultivars grown with or without watering to assess the genetic variation for polyphenol composition and its modulation by irrigation, in two successive vintages (2014–2015. Distribution of berry weights and δ13C values showed that non irrigated vines were subjected to a marked water stress in 2014 and to a very limited one in 2015. Metabolomics analysis of the polyphenol composition and chemometrics analysis of this data demonstrated an influence of water stress on the biosynthesis of different polyphenol classes and cultivar differences in metabolic response to water deficit. Correlation networks gave insight on the relationships between the different polyphenol metabolites and related biosynthetic pathways. They also

  8. Metabolomics-Based Elucidation of Active Metabolic Pathways in Erythrocytes and HSC-Derived Reticulocytes.

    Science.gov (United States)

    Srivastava, Anubhav; Evans, Krystal J; Sexton, Anna E; Schofield, Louis; Creek, Darren J

    2017-04-07

    A detailed analysis of the metabolic state of human-stem-cell-derived erythrocytes allowed us to characterize the existence of active metabolic pathways in younger reticulocytes and compare them to mature erythrocytes. Using high-resolution LC-MS-based untargeted metabolomics, we found that reticulocytes had a comparatively much richer repertoire of metabolites, which spanned a range of metabolite classes. An untargeted metabolomics analysis using stable-isotope-labeled glucose showed that only glycolysis and the pentose phosphate pathway actively contributed to the biosynthesis of metabolites in erythrocytes, and these pathways were upregulated in reticulocytes. Most metabolite species found to be enriched in reticulocytes were residual pools of metabolites produced by earlier erythropoietic processes, and their systematic depletion in mature erythrocytes aligns with the simplification process, which is also seen at the cellular and the structural level. Our work shows that high-resolution LC-MS-based untargeted metabolomics provides a global coverage of the biochemical species that are present in erythrocytes. However, the incorporation of stable isotope labeling provides a more accurate description of the active metabolic processes that occur in each developmental stage. To our knowledge, this is the first detailed characterization of the active metabolic pathways of the erythroid lineage, and it provides a rich database for understanding the physiology of the maturation of reticulocytes into mature erythrocytes.

  9. Mass spectrometry-based metabolomics: applications to biomarker and metabolic pathway research.

    Science.gov (United States)

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

    2016-01-01

    Mass spectrometry-based metabolomics has become increasingly popular in molecular medicine. High-definition mass spectrometry (MS), coupled with pattern recognition methods, have been carried out to obtain comprehensive metabolite profiling and metabolic pathway of large biological datasets. This sets the scene for a new and powerful diagnostic approach. Analysis of the key metabolites in body fluids has become an important part of improving disease diagnosis. With technological advances in analytical techniques, the ability to measure low-molecular-weight metabolites in bio-samples provides a powerful platform for identifying metabolites that are uniquely correlated with a specific human disease. MS-based metabolomics can lead to enhanced understanding of disease mechanisms and to new diagnostic markers and has a strong potential to contribute to improving early diagnosis of diseases. This review will highlight the importance and benefit with certain characteristic examples of MS-metabolomics for identifying metabolic pathways and metabolites that accurately screen for potential diagnostic biomarkers of diseases. Copyright © 2015 John Wiley & Sons, Ltd.

  10. UHPLC-Q-Orbitrap-HRMS-based global metabolomics reveal metabolome modifications in plasma of young women after cranberry juice consumption.

    Science.gov (United States)

    Liu, Haiyan; Garrett, Timothy J; Su, Zhihua; Khoo, Christina; Gu, Liwei

    2017-07-01

    Plasma metabolome in young women following cranberry juice consumption were investigated using a global UHPLC-Q-Orbitrap-HRMS approach. Seventeen female college students, between 21 and 29 years old, were given either cranberry juice or apple juice for three days using a cross-over design. Plasma samples were collected before and after juice consumption. Plasma metabolomes were analyzed using UHPLC-Q-Orbitrap-HRMS followed by orthogonal partial least squares-discriminant analyses (OPLS-DA). S-plot was used to identify discriminant metabolites. Validated OPLS-DA analyses showed that the plasma metabolome in young women, including both exogenous and endogenous metabolites, were altered following cranberry juice consumption. Cranberry juice caused increases of exogenous metabolites including quinic acid, vanilloloside, catechol sulfate, 3,4-dihydroxyphenyl ethanol sulfate, coumaric acid sulfate, ferulic acid sulfate, 5-(trihydroxphenyl)-gamma-valerolactone, 3-(hydroxyphenyl)proponic acid, hydroxyphenylacetic acid and trihydroxybenzoic acid. In addition, the plasma levels of endogenous metabolites including citramalic acid, aconitic acid, hydroxyoctadecanoic acid, hippuric acid, 2-hydroxyhippuric acid, vanilloylglycine, 4-acetamido-2-aminobutanoic acid, dihydroxyquinoline, and glycerol 3-phosphate were increased in women following cranberry juice consumption. The metabolic differences and discriminant metabolites observed in this study may serve as biomarkers of cranberry juice consumption and explain its health promoting properties in human. Copyright © 2017 Elsevier Inc. All rights reserved.

  11. Urine metabolite analysis as a function of deoxynivalenol exposure: an NMR-based metabolomics investigation.

    Science.gov (United States)

    Hopton, R P; Turner, E; Burley, V J; Turner, P C; Fisher, J

    2010-02-01

    Deoxynivalenol (DON) is a toxic fungal metabolite that frequently contaminates cereal crops including wheat, maize and barley. Despite knowledge of frequent exposure through diet, our understanding of the potential consequences of human exposure remains limited, in part due to the lack of validated exposure biomarkers. In this study, we interrogated the urinary metabolome using nuclear magnetic resonance (NMR) spectroscopy to compare individuals with known low and high DON exposure through consumption of their normal diet. Urine samples from 22 adults from the UK (seven males, 15 females; age range = 21-59 years) had previously determined urinary DON levels using an established liquid chromatography-mass spectrometry (LC-MS) assay. Urine samples were subsequently analysed using an NMR-based metabolomics approach coupled with multivariate statistical analysis. Metabolic profiling suggested that hippurate levels could be used to distinguish between groups with low (3.6 ng DON mg(-1) creatinine: 95% CI = 2.6, 5.0 ng mg(-1)) and high (11.1 ng mg(-1): 95% CI = 8.1, 15.5 ng mg(-1)) DON exposure, with the concentration of hippurate being significantly (1.5 times) higher for people with high DON exposure than for those with low DON exposure (p = 0.047). This, to our knowledge, is the first report of a metabolomics-derived biomarker of DON exposure in humans.

  12. Strategy for nuclear-magnetic-resonance-based metabolomics of human feces

    DEFF Research Database (Denmark)

    Lamichhane, Santosh; Yde, Christian Clement; Schmedes, Mette Søndergaard

    2015-01-01

    of fresh feces by NMR-based metabolomics. The evaluation of extraction solvents showed that buffer extraction is a suitable approach to extract metabolic information in feces. So, the effects of weight-to-buffer (Wf:Vb) combinations and the effect of sonication and freeze-thaw cycles on the reproducibility......, chemical shift variability, and signal to noise ratio (SNR) of the 1H NMR spectra were evaluated. Based on our results, we suggest that fresh fecal extraction with a Wf:Vb ratio of 1:2 may be the optimum choice to determine the overall metabolite composition of feces. In fact, more than 60 metabolites have...

  13. PLS-based and regularization-based methods for the selection of relevant variables in non-targeted metabolomics data

    Directory of Open Access Journals (Sweden)

    Renata Bujak

    2016-07-01

    Full Text Available Non-targeted metabolomics constitutes a part of systems biology and aims to determine many metabolites in complex biological samples. Datasets obtained in non-targeted metabolomics studies are multivariate and high-dimensional due to the sensitivity of mass spectrometry-based detection methods as well as complexity of biological matrices. Proper selection of variables which contribute into group classification is a crucial step, especially in metabolomics studies which are focused on searching for disease biomarker candidates. In the present study, three different statistical approaches were tested using two metabolomics datasets (RH and PH study. Orthogonal projections to latent structures-discriminant analysis (OPLS-DA without and with multiple testing correction as well as least absolute shrinkage and selection operator (LASSO were tested and compared. For the RH study, OPLS-DA model built without multiple testing correction, selected 46 and 218 variables based on VIP criteria using Pareto and UV scaling, respectively. In the case of the PH study, 217 and 320 variables were selected based on VIP criteria using Pareto and UV scaling, respectively. In the RH study, OPLS-DA model built with multiple testing correction, selected 4 and 19 variables as statistically significant in terms of Pareto and UV scaling, respectively. For PH study, 14 and 18 variables were selected based on VIP criteria in terms of Pareto and UV scaling, respectively. Additionally, the concept and fundaments of the least absolute shrinkage and selection operator (LASSO with bootstrap procedure evaluating reproducibility of results, was demonstrated. In the RH and PH study, the LASSO selected 14 and 4 variables with reproducibility between 99.3% and 100%. However, apart from the popularity of PLS-DA and OPLS-DA methods in metabolomics, it should be highlighted that they do not control type I or type II error, but only arbitrarily establish a cut-off value for PLS-DA loadings

  14. Impact of soil warming on the plant metabolome of Icelandic grasslands

    Czech Academy of Sciences Publication Activity Database

    Gargallo-Garriga, A.; Ayala-Roque, M.; Sardans, J.; Bartrons, M.; Granda, V.; Sigurdsson, B. D.; Leblans, N. I.W.; Oravec, Michal; Urban, Otmar; Janssens, I. A.; Peñuelas, J.

    2017-01-01

    Roč. 7, č. 3 (2017), č. článku 44. E-ISSN 2218-1989 R&D Projects: GA MŠk(CZ) LM2015061; GA MŠk(CZ) LO1415 Institutional support: RVO:86652079 Keywords : Climate change * Geothermal bedrock channels * Grassland * Iceland * Metabolome * Warming Subject RIV: EH - Ecology, Behaviour OBOR OECD: Environmental sciences (social aspects to be 5.7)

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

    Science.gov (United States)

    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.

  16. Bio-effectors from waste materials as growth promoters for tomato plants, an agronomic and metabolomic study

    Science.gov (United States)

    Abou Chehade, Lara; Chami, Ziad Al; De Pascali, Sandra; Cavoski, Ivana; Fanizzi, Francesco Paolo

    2015-04-01

    In organic farming, where nutrient management is constrained and sustainability is claimed, bio-effectors pave their way. Considering selected bio-effectors, this study integrates metabolomics to agronomy in depicting induced relevant phenomena. Extracts of three agro-industrial wastes (Lemon processing residues, Fennel processing residues and Brewer's spent grain) are being investigated as sources of bio-effectors for the third trial consequently. Corresponding individual and mixture aqueous extracts are assessed for their synergistic and/or single agronomic and qualitative performances on soil-grown tomato, compared to both a control and humic acid treatments. A metabolomic profiling of tomato fruits via the Proton Nuclear Magnetic Resonance (NMR) spectroscopy, as holistic indicator of fruit quality and extract-induced responses, complements crop productivity and organoleptic/nutritional qualitative analyses. Results are expected to show mainly an enhancement of the fruit qualitative traits, and to confirm partly the previous results of better crop productivity and metabolism enhancement. Waste-derived bio-effectors could be, accordingly, demonstrated as potential candidates of plant-enhancing substances. Keywords: bio-effectors, organic farming, agro-industrial wastes, nuclear magnetic resonance (NMR), tomato.

  17. Mass Spectrometry-Based Metabolomic and Proteomic Strategies in Organic Acidemias

    Directory of Open Access Journals (Sweden)

    Esther Imperlini

    2016-01-01

    Full Text Available Organic acidemias (OAs are inherited metabolic disorders caused by deficiency of enzymatic activities in the catabolism of amino acids, carbohydrates, or lipids. These disorders result in the accumulation of mono-, di-, or tricarboxylic acids, generally referred to as organic acids. The OA outcomes can involve different organs and/or systems. Some OA disorders are easily managed if promptly diagnosed and treated, whereas, in others cases, such as propionate metabolism-related OAs (propionic acidemia, PA; methylmalonic acidemia, MMA, neither diet, vitamin therapy, nor liver transplantation appears to prevent multiorgan impairment. Here, we review the recent developments in dissecting molecular bases of OAs by using integration of mass spectrometry- (MS- based metabolomic and proteomic strategies. MS-based techniques have facilitated the rapid and economical evaluation of a broad spectrum of metabolites in various body fluids, also collected in small samples, like dried blood spots. This approach has enabled the timely diagnosis of OAs, thereby facilitating early therapeutic intervention. Besides providing an overview of MS-based approaches most frequently used to study the molecular mechanisms underlying OA pathophysiology, we discuss the principal challenges of metabolomic and proteomic applications to OAs.

  18. 2-Hydrazinoquinoline as a Derivatization Agent for LC-MS-Based Metabolomic Investigation of Diabetic Ketoacidosis

    Science.gov (United States)

    Lu, Yuwei; Yao, Dan; Chen, Chi

    2013-01-01

    Short-chain carboxylic acids, aldehydes and ketones are products and regulators of many important metabolic pathways. Their levels in biofluids and tissues reflect the status of specific metabolic reactions, the homeostasis of the whole metabolic system and the wellbeing of a biological entity. In this study, the use of 2-hydrazinoquinoline (HQ) as a novel derivatization agent was explored and optimized for simultaneous liquid chromatography-mass spectrometry (LC-MS) analysis of carboxylic acids, aldehydes and ketones in biological samples. The formation of carboxylic acid derivative is attributed to the esterification reaction between HQ and a carboxyl group, while the production of aldehyde and ketone derivatives is through the formation of Schiff bases between HQ and a carbonyl group. The compatibility of HQ with biological samples was demonstrated by derivatizing urine, serum and liver extract samples. Using this HQ-based approach, the kinetics of type 1 diabetes-induced metabolic changes was characterized by the LC-MS-based metabolomic analysis of urine samples from streptozotocin (STZ)-treated mice. Subsequently, carboxylic acid, aldehyde and ketone metabolites associated with STZ-elicited disruption of nutrient and energy metabolism were conveniently identified and elucidated. Overall, HQ derivatization of carboxylic acids, aldehydes and ketones could serve as a useful tool for the LC-MS-based metabolomic investigation of endogenous metabolism. PMID:24958262

  19. Targeted metabolomics shows plasticity in the evolution of signaling lipids and uncovers old and new endocannabinoids in the plant kingdom.

    Science.gov (United States)

    Gachet, María Salomé; Schubert, Alexandra; Calarco, Serafina; Boccard, Julien; Gertsch, Jürg

    2017-01-25

    The remarkable absence of arachidonic acid (AA) in seed plants prompted us to systematically study the presence of C20 polyunsaturated fatty acids, stearic acid, oleic acid, jasmonic acid (JA), N-acylethanolamines (NAEs) and endocannabinoids (ECs) in 71 plant species representative of major phylogenetic clades. Given the difficulty of extrapolating information about lipid metabolites from genetic data we employed targeted metabolomics using LC-MS/MS and GC-MS to study these signaling lipids in plant evolution. Intriguingly, the distribution of AA among the clades showed an inverse correlation with JA which was less present in algae, bryophytes and monilophytes. Conversely, ECs co-occurred with AA in algae and in the lower plants (bryophytes and monilophytes), thus prior to the evolution of cannabinoid receptors in Animalia. We identified two novel EC-like molecules derived from the eicosatetraenoic acid juniperonic acid, an omega-3 structural isomer of AA, namely juniperoyl ethanolamide and 2-juniperoyl glycerol in gymnosperms, lycophytes and few monilophytes. Principal component analysis of the targeted metabolic profiles suggested that distinct NAEs may occur in different monophyletic taxa. This is the first report on the molecular phylogenetic distribution of apparently ancient lipids in the plant kingdom, indicating biosynthetic plasticity and potential physiological roles of EC-like lipids in plants.

  20. QCScreen: a software tool for data quality control in LC-HRMS based metabolomics.

    Science.gov (United States)

    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. [Metabolomics in research of phytotherapeutics].

    Science.gov (United States)

    Kráfová, Katarina; Jampílek, Josef; Ostrovský, Ivan

    2012-02-01

    Pharmaceutical and food industries are increasingly focused on the great potential of plant secondary metabolites or natural substances which can be used as therapeutics or model compounds for development of new drugs. The paper is devoted to the use of metabolomics, metabolic profiling and metabolic "fingerprint" for the identification of individual active phyto-substances in plant extracts, in profiling of unique groups of plant secondary metabolites that can be used to improve the classification of several species of medicinal plants as well as for a better characterization and quality control of medicinal extracts, tinctures and phytotherapeutic products prepared from these plants. Combined analytical methods and multivariate statistical analysis are used for metabolite identification. Using this approach, medicinal plants are evaluated not only on the basis of a limited number of pharmacologically important metabolites but also based on the fingerprints of minor metabolites and bioactive molecules.

  2. Stable isotope- and mass spectrometry-based metabolomics as tools in drug metabolism: a study expanding tempol pharmacology.

    Science.gov (United States)

    Li, Fei; Pang, Xiaoyan; Krausz, Kristopher W; Jiang, Changtao; Chen, Chi; Cook, John A; Krishna, Murali C; Mitchell, James B; Gonzalez, Frank J; Patterson, Andrew D

    2013-03-01

    The application of mass spectrometry-based metabolomics in the field of drug metabolism has yielded important insights not only into the metabolic routes of drugs but has provided unbiased, global perspectives of the endogenous metabolome that can be useful for identifying biomarkers associated with mechanism of action, efficacy, and toxicity. In this report, a stable isotope- and mass spectrometry-based metabolomics approach that captures both drug metabolism and changes in the endogenous metabolome in a single experiment is described. Here the antioxidant drug tempol (4-hydroxy-2,2,6,6-tetramethylpiperidine-N-oxyl) was chosen because its mechanism of action is not completely understood and its metabolic fate has not been studied extensively. Furthermore, its small size (MW = 172.2) and chemical composition (C(9)H(18)NO(2)) make it challenging to distinguish from endogenous metabolites. In this study, mice were dosed with tempol or deuterated tempol (C(9)D(17)HNO(2)) and their urine was profiled using ultraperformance liquid chromatography coupled with quadrupole time-of-flight mass spectrometry. Principal component analysis of the urinary metabolomics data generated a Y-shaped scatter plot containing drug metabolites (protonated and deuterated) that were clearly distinct from the endogenous metabolites. Ten tempol drug metabolites, including eight novel metabolites, were identified. Phase II metabolism was the major metabolic pathway of tempol in vivo, including glucuronidation and glucosidation. Urinary endogenous metabolites significantly elevated by tempol treatment included 2,8-dihydroxyquinoline (8.0-fold, P tempol treatment including pantothenic acid (1.3-fold, P < 0.05) and isobutrylcarnitine (5.3-fold, P < 0.01). This study underscores the power of a stable isotope- and mass spectrometry-based metabolomics in expanding the view of drug pharmacology.

  3. Influence of Freezing and Storage Procedure on Human Urine Samples in NMR-Based Metabolomics

    Directory of Open Access Journals (Sweden)

    Burkhard Luy

    2013-04-01

    Full Text Available It is consensus in the metabolomics community that standardized protocols should be followed for sample handling, storage and analysis, as it is of utmost importance to maintain constant measurement conditions to identify subtle biological differences. The aim of this work, therefore, was to systematically investigate the influence of freezing procedures and storage temperatures and their effect on NMR spectra as a potentially disturbing aspect for NMR-based metabolomics studies. Urine samples were collected from two healthy volunteers, centrifuged and divided into aliquots. Urine aliquots were frozen either at −20 °C, on dry ice, at −80 °C or in liquid nitrogen and then stored at −20 °C, −80 °C or in liquid nitrogen vapor phase for 1–5 weeks before NMR analysis. Results show spectral changes depending on the freezing procedure, with samples frozen on dry ice showing the largest deviations. The effect was found to be based on pH differences, which were caused by variations in CO2 concentrations introduced by the freezing procedure. Thus, we recommend that urine samples should be frozen at −20 °C and transferred to lower storage temperatures within one week and that freezing procedures should be part of the publication protocol.

  4. The Chemical Translation Service—a web-based tool to improve standardization of metabolomic reports

    Science.gov (United States)

    Wohlgemuth, Gert; Haldiya, Pradeep Kumar; Willighagen, Egon; Kind, Tobias; Fiehn, Oliver

    2010-01-01

    Summary: Metabolomic publications and databases use different database identifiers or even trivial names which disable queries across databases or between studies. The best way to annotate metabolites is by chemical structures, encoded by the International Chemical Identifier code (InChI) or InChIKey. We have implemented a web-based Chemical Translation Service that performs batch conversions of the most common compound identifiers, including CAS, CHEBI, compound formulas, Human Metabolome Database HMDB, InChI, InChIKey, IUPAC name, KEGG, LipidMaps, PubChem CID+SID, SMILES and chemical synonym names. Batch conversion downloads of 1410 CIDs are performed in 2.5 min. Structures are automatically displayed. Implementation: The software was implemented in Groovy and JAVA, the web frontend was implemented in GRAILS and the database used was PostgreSQL. Availability: The source code and an online web interface are freely available. Chemical Translation Service (CTS): http://cts.fiehnlab.ucdavis.edu Contact: ofiehn@ucdavis.edu PMID:20829444

  5. The Chemical Translation Service--a web-based tool to improve standardization of metabolomic reports.

    Science.gov (United States)

    Wohlgemuth, Gert; Haldiya, Pradeep Kumar; Willighagen, Egon; Kind, Tobias; Fiehn, Oliver

    2010-10-15

    Metabolomic publications and databases use different database identifiers or even trivial names which disable queries across databases or between studies. The best way to annotate metabolites is by chemical structures, encoded by the International Chemical Identifier code (InChI) or InChIKey. We have implemented a web-based Chemical Translation Service that performs batch conversions of the most common compound identifiers, including CAS, CHEBI, compound formulas, Human Metabolome Database HMDB, InChI, InChIKey, IUPAC name, KEGG, LipidMaps, PubChem CID+SID, SMILES and chemical synonym names. Batch conversion downloads of 1410 CIDs are performed in 2.5 min. Structures are automatically displayed. The software was implemented in Groovy and JAVA, the web frontend was implemented in GRAILS and the database used was PostgreSQL. The source code and an online web interface are freely available. Chemical Translation Service (CTS): http://cts.fiehnlab.ucdavis.edu ofiehn@ucdavis.edu

  6. Overexpression of ORCA3 and G10H in Catharanthus roseus Plants Regulated Alkaloid Biosynthesis and Metabolism Revealed by NMR-Metabolomics

    Science.gov (United States)

    Pan, Qifang; Wang, Quan; Yuan, Fang; Xing, Shihai; Zhao, Jingya; Choi, Young Hae; Verpoorte, Robert; Tian, Yuesheng; Wang, Guofeng; Tang, Kexuan

    2012-01-01

    In order to improve the production of the anticancer dimeric indole alkaloids in Catharanthuse roseus, much research has been dedicated to culturing cell lines, hairy roots, and efforts to elucidate the regulation of the monoterpenoid indole alkaloid (MIA) biosynthesis. In this study, the ORCA3 (Octadecanoid-derivative Responsive Catharanthus AP2-domain) gene alone or integrated with the G10H (geraniol 10-hydroxylase) gene were first introduced into C. roseus plants. Transgenic C. roseus plants overexpressing ORCA3 alone (OR lines), or co-overexpressing G10H and ORCA3 (GO lines) were obtained by genetic modification. ORCA3 overexpression induced an increase of AS, TDC, STR and D4H transcripts but did not affect CRMYC2 and G10H transcription. G10H transcripts showed a significant increase under G10H and ORCA3 co-overexpression. ORCA3 and G10H overexpression significantly increased the accumulation of strictosidine, vindoline, catharanthine and ajmalicine but had limited effects on anhydrovinblastine and vinblastine levels. NMR-based metabolomics confirmed the higher accumulation of monomeric indole alkaloids in OR and GO lines. Multivariate data analysis of 1H NMR spectra showed change of amino acid, organic acid, sugar and phenylpropanoid levels in both OR and GO lines compared to the controls. The result indicated that enhancement of MIA biosynthesis by ORCA3 and G10H overexpression might affect other metabolic pathways in the plant metabolism of C. roseus. PMID:22916202

  7. Overexpression of ORCA3 and G10H in Catharanthus roseus plants regulated alkaloid biosynthesis and metabolism revealed by NMR-metabolomics.

    Directory of Open Access Journals (Sweden)

    Qifang Pan

    Full Text Available In order to improve the production of the anticancer dimeric indole alkaloids in Catharanthuse roseus, much research has been dedicated to culturing cell lines, hairy roots, and efforts to elucidate the regulation of the monoterpenoid indole alkaloid (MIA biosynthesis. In this study, the ORCA3 (Octadecanoid-derivative Responsive Catharanthus AP2-domain gene alone or integrated with the G10H (geraniol 10-hydroxylase gene were first introduced into C. roseus plants. Transgenic C. roseus plants overexpressing ORCA3 alone (OR lines, or co-overexpressing G10H and ORCA3 (GO lines were obtained by genetic modification. ORCA3 overexpression induced an increase of AS, TDC, STR and D4H transcripts but did not affect CRMYC2 and G10H transcription. G10H transcripts showed a significant increase under G10H and ORCA3 co-overexpression. ORCA3 and G10H overexpression significantly increased the accumulation of strictosidine, vindoline, catharanthine and ajmalicine but had limited effects on anhydrovinblastine and vinblastine levels. NMR-based metabolomics confirmed the higher accumulation of monomeric indole alkaloids in OR and GO lines. Multivariate data analysis of (1H NMR spectra showed change of amino acid, organic acid, sugar and phenylpropanoid levels in both OR and GO lines compared to the controls. The result indicated that enhancement of MIA biosynthesis by ORCA3 and G10H overexpression might affect other metabolic pathways in the plant metabolism of C. roseus.

  8. Rice suspension cultured cells are evaluated as a model system to study salt responsive networks in plants using a combined proteomic and metabolomic profiling approach.

    Science.gov (United States)

    Liu, Dawei; Ford, Kristina L; Roessner, Ute; Natera, Siria; Cassin, Andrew M; Patterson, John H; Bacic, Antony

    2013-06-01

    Salinity is one of the major abiotic stresses affecting plant productivity but surprisingly, a thorough understanding of the salt-responsive networks responsible for sustaining growth and maintaining crop yield remains a significant challenge. Rice suspension culture cells (SCCs), a single cell type, were evaluated as a model system as they provide a ready source of a homogenous cell type and avoid the complications of multicellular tissue types in planta. A combination of growth performance, and transcriptional analyses using known salt-induced genes was performed on control and 100 mM NaCl cultured cells to validate the biological system. Protein profiling was conducted using both DIGE- and iTRAQ-based proteomics approaches. In total, 106 proteins were identified in DIGE experiments and 521 proteins in iTRAQ experiments with 58 proteins common to both approaches. Metabolomic analysis provided insights into both developmental changes and salt-induced changes of rice SCCs at the metabolite level; 134 known metabolites were identified, including 30 amines and amides, 40 organic acids, 40 sugars, sugar acids and sugar alcohols, 21 fatty acids and sterols, and 3 miscellaneous compounds. Our results from proteomic and metabolomic studies indicate that the salt-responsive networks of rice SCCs are extremely complex and share some similarities with thee cellular responses observed in planta. For instance, carbohydrate and energy metabolism pathways, redox signaling pathways, auxin/indole-3-acetic acid pathways and biosynthesis pathways for osmoprotectants are all salt responsive in SCCs enabling cells to maintain cellular function under stress condition. These data are discussed in the context of our understanding of in planta salt-responses. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  9. Comparison of Salt Tolerance inSojaBased on Metabolomics of Seedling Roots.

    Science.gov (United States)

    Li, Mingxia; Guo, Rui; Jiao, Yang; Jin, Xiaofei; Zhang, Haiyan; Shi, Lianxuan

    2017-01-01

    Soybean is an important economic crop that is continually threatened by abiotic stresses, especially salt stress. Wild soybean is an important germplasm resource for the breeding of cultivated soybean. The root system plays a very important role in plant salt tolerance. To explore the salt tolerance-related mechanisms among Soja , we have demonstrated the seedling roots' growth and metabolomics in wild soybean, semi-wild soybean, and cultivated soybean under two types of salt stress by using gas chromatography-mass spectrometry. We characterized 47 kinds of differential metabolites under neutral salt stress, and isoleucine, serine, l-allothreonine, glutamic acid, phenylalanine, asparagines, aspartic acid, pentadecanoic acid, lignoceric acid, oleic acid, galactose, tagatose, d-arabitol, dihydroxyacetone, 3-hydroxybutyric acid, and glucuronic acid increased significantly in the roots of wild soybean seedlings. However, these metabolites were suppressed in semi-wild and cultivated soybeans. Amino acid, fatty acid, sugars, and organic acid synthesis and the secondary metabolism of antioxidants increased significantly in the roots of wild soybean seedling. Under alkaline salt stress, wild soybean contained significantly higher amounts of proline, glutamic acid, aspartic acid, l-allothreonine, isoleucine, serine, alanine, arachidic acid, oleic acid, cis-gondoic acid, fumaric acid, l-malic acid, citric acid, malonic acid, gluconic acid, 5-methoxytryptamine, salicylic acid, and fluorene than semi-wild and cultivated soybeans. Our study demonstrated that carbon and nitrogen metabolism, and the tricarboxylic acid (TCA) cycle and receiver operating characteristics (especially the metabolism of phenolic substances) of the seedling roots were important to resisting salt stress and showed a regular decreasing trend from wild soybean to cultivated soybean. The metabolomics's changes were critical factors in the evolution of salt tolerance among Soja . This study provides new

  10. Comparison of Salt Tolerance in Soja Based on Metabolomics of Seedling Roots

    Science.gov (United States)

    Li, Mingxia; Guo, Rui; Jiao, Yang; Jin, Xiaofei; Zhang, Haiyan; Shi, Lianxuan

    2017-01-01

    Soybean is an important economic crop that is continually threatened by abiotic stresses, especially salt stress. Wild soybean is an important germplasm resource for the breeding of cultivated soybean. The root system plays a very important role in plant salt tolerance. To explore the salt tolerance-related mechanisms among Soja, we have demonstrated the seedling roots' growth and metabolomics in wild soybean, semi-wild soybean, and cultivated soybean under two types of salt stress by using gas chromatography-mass spectrometry. We characterized 47 kinds of differential metabolites under neutral salt stress, and isoleucine, serine, l-allothreonine, glutamic acid, phenylalanine, asparagines, aspartic acid, pentadecanoic acid, lignoceric acid, oleic acid, galactose, tagatose, d-arabitol, dihydroxyacetone, 3-hydroxybutyric acid, and glucuronic acid increased significantly in the roots of wild soybean seedlings. However, these metabolites were suppressed in semi-wild and cultivated soybeans. Amino acid, fatty acid, sugars, and organic acid synthesis and the secondary metabolism of antioxidants increased significantly in the roots of wild soybean seedling. Under alkaline salt stress, wild soybean contained significantly higher amounts of proline, glutamic acid, aspartic acid, l-allothreonine, isoleucine, serine, alanine, arachidic acid, oleic acid, cis-gondoic acid, fumaric acid, l-malic acid, citric acid, malonic acid, gluconic acid, 5-methoxytryptamine, salicylic acid, and fluorene than semi-wild and cultivated soybeans. Our study demonstrated that carbon and nitrogen metabolism, and the tricarboxylic acid (TCA) cycle and receiver operating characteristics (especially the metabolism of phenolic substances) of the seedling roots were important to resisting salt stress and showed a regular decreasing trend from wild soybean to cultivated soybean. The metabolomics's changes were critical factors in the evolution of salt tolerance among Soja. This study provides new

  11. Comparison of Salt Tolerance in Soja Based on Metabolomics of Seedling Roots

    Directory of Open Access Journals (Sweden)

    Mingxia Li

    2017-06-01

    Full Text Available Soybean is an important economic crop that is continually threatened by abiotic stresses, especially salt stress. Wild soybean is an important germplasm resource for the breeding of cultivated soybean. The root system plays a very important role in plant salt tolerance. To explore the salt tolerance-related mechanisms among Soja, we have demonstrated the seedling roots' growth and metabolomics in wild soybean, semi-wild soybean, and cultivated soybean under two types of salt stress by using gas chromatography-mass spectrometry. We characterized 47 kinds of differential metabolites under neutral salt stress, and isoleucine, serine, l-allothreonine, glutamic acid, phenylalanine, asparagines, aspartic acid, pentadecanoic acid, lignoceric acid, oleic acid, galactose, tagatose, d-arabitol, dihydroxyacetone, 3-hydroxybutyric acid, and glucuronic acid increased significantly in the roots of wild soybean seedlings. However, these metabolites were suppressed in semi-wild and cultivated soybeans. Amino acid, fatty acid, sugars, and organic acid synthesis and the secondary metabolism of antioxidants increased significantly in the roots of wild soybean seedling. Under alkaline salt stress, wild soybean contained significantly higher amounts of proline, glutamic acid, aspartic acid, l-allothreonine, isoleucine, serine, alanine, arachidic acid, oleic acid, cis-gondoic acid, fumaric acid, l-malic acid, citric acid, malonic acid, gluconic acid, 5-methoxytryptamine, salicylic acid, and fluorene than semi-wild and cultivated soybeans. Our study demonstrated that carbon and nitrogen metabolism, and the tricarboxylic acid (TCA cycle and receiver operating characteristics (especially the metabolism of phenolic substances of the seedling roots were important to resisting salt stress and showed a regular decreasing trend from wild soybean to cultivated soybean. The metabolomics's changes were critical factors in the evolution of salt tolerance among Soja. This study

  12. Quality assurance of metabolomics.

    Science.gov (United States)

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

    2015-01-01

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

  13. MetaQuant: a tool for the automatic quantification of GC/MS-based metabolome data.

    Science.gov (United States)

    Bunk, Boyke; Kucklick, Martin; Jonas, Rochus; Münch, Richard; Schobert, Max; Jahn, Dieter; Hiller, Karsten

    2006-12-01

    MetaQuant is a Java-based program for the automatic and accurate quantification of GC/MS-based metabolome data. In contrast to other programs MetaQuant is able to quantify hundreds of substances simultaneously with minimal manual intervention. The integration of a self-acting calibration function allows the parallel and fast calibration for several metabolites simultaneously. Finally, MetaQuant is able to import GC/MS data in the common NetCDF format and to export the results of the quantification into Systems Biology Markup Language (SBML), Comma Separated Values (CSV) or Microsoft Excel (XLS) format. MetaQuant is written in Java and is available under an open source license. Precompiled packages for the installation on Windows or Linux operating systems are freely available for download. The source code as well as the installation packages are available at http://bioinformatics.org/metaquant

  14. Metabolomic Profiling of Bradyrhizobium diazoefficiens-Induced Root Nodules Reveals Both Host Plant-Specific and Developmental Signatures

    Directory of Open Access Journals (Sweden)

    Martina Lardi

    2016-05-01

    Full Text Available Bradyrhizobium diazoefficiens is a nitrogen-fixing endosymbiont, which can grow inside root-nodule cells of the agriculturally important soybean and other host plants. Our previous studies described B. diazoefficiens host-specific global expression changes occurring during legume infection at the transcript and protein level. In order to further characterize nodule metabolism, we here determine by flow injection–time-of-flight mass spectrometry analysis the metabolome of (i nodules and roots from four different B. diazoefficiens host plants; (ii soybean nodules harvested at different time points during nodule development; and (iii soybean nodules infected by two strains mutated in key genes for nitrogen fixation, respectively. Ribose (soybean, tartaric acid (mungbean, hydroxybutanoyloxybutanoate (siratro and catechol (cowpea were among the metabolites found to be specifically elevated in one of the respective host plants. While the level of C4-dicarboxylic acids decreased during soybean nodule development, we observed an accumulation of trehalose-phosphate at 21 days post infection (dpi. Moreover, nodules from non-nitrogen-fixing bacteroids (nifA and nifH mutants showed specific metabolic alterations; these were also supported by independent transcriptomics data. The alterations included signs of nitrogen limitation in both mutants, and an increased level of a phytoalexin in nodules induced by the nifA mutant, suggesting that the tissue of these nodules exhibits defense and stress reactions.

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

    Directory of Open Access Journals (Sweden)

    Shin Nishiumi

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

  16. UPLC/Q-TOF MS-based metabolomics and qRT-PCR in enzyme gene screening with key role in triterpenoid saponin biosynthesis of Polygala tenuifolia.

    Directory of Open Access Journals (Sweden)

    Fusheng Zhang

    Full Text Available The dried root of Polygala tenuifolia, named Radix Polygalae, is a well-known traditional Chinese medicine. Triterpenoid saponins are some of the most important components of Radix Polygalae extracts and are widely studied because of their valuable pharmacological properties. However, the relationship between gene expression and triterpenoid saponin biosynthesis in P. tenuifolia is unclear.In this study, ultra-performance liquid chromatography (UPLC coupled with quadrupole time-of-flight mass spectrometry (Q-TOF MS-based metabolomic analysis was performed to identify and quantify the different chemical constituents of the roots, stems, leaves, and seeds of P. tenuifolia. A total of 22 marker compounds (VIP>1 were explored, and significant differences in all 7 triterpenoid saponins among the different tissues were found. We also observed an efficient reference gene GAPDH for different tissues in this plant and determined the expression level of some genes in the triterpenoid saponin biosynthetic pathway. Results showed that MVA pathway has more important functions in the triterpenoid saponin biosynthesis of P. tenuifolia. The expression levels of squalene synthase (SQS, squalene monooxygenase (SQE, and beta-amyrin synthase (β-AS were highly correlated with the peak area intensity of triterpenoid saponins compared with data from UPLC/Q-TOF MS-based metabolomic analysis.This finding suggested that a combination of UPLC/Q-TOF MS-based metabolomics and gene expression analysis can effectively elucidate the mechanism of triterpenoid saponin biosynthesis and can provide useful information on gene discovery. These findings can serve as a reference for using the overexpression of genes encoding for SQS, SQE, and/or β-AS to increase the triterpenoid saponin production of P. tenuifolia.

  17. 1H NMR-based metabolomics of time-dependent responses of Eisenia fetida to sub-lethal phenanthrene exposure

    International Nuclear Information System (INIS)

    Lankadurai, Brian P.; Wolfe, David M.; Simpson, Andre J.; Simpson, Myrna J.

    2011-01-01

    1 H NMR-based metabolomics was used to examine the response of the earthworm Eisenia fetida after exposure to sub-lethal concentrations of phenanthrene over time. Earthworms were exposed to 0.025 mg/cm 2 of phenanthrene (1/64th of the LC 50 ) via contact tests over four days. Earthworm tissues were extracted using a mixture of chloroform, methanol and water, resulting in polar and non-polar fractions that were analyzed by 1 H NMR after one, two, three and four days. NMR-based metabolomic analyses revealed heightened E. fetida responses with longer phenanthrene exposure times. Amino acids alanine and glutamate, the sugar maltose, the lipids cholesterol and phosphatidylcholine emerged as potential indicators of phenanthrene exposure. The conversion of succinate to fumarate in the Krebs cycle was also interrupted by phenanthrene. Therefore, this study shows that NMR-based metabolomics is a powerful tool for elucidating time-dependent relationships in addition to the mode of toxicity of phenanthrene in earthworm exposure studies. - Highlights: → NMR-based earthworm metabolomic analysis of the mode of action of phenanthrene is presented. → The earthworm species E. fetida were exposed to sub-lethal phenanthrene concentrations. → Both polar and non-polar metabolites of E. fetida tissue extracts were analyzed by 1 H NMR. → Longer phenanthrene exposure times resulted in heightened earthworm responses. → An interruption of the Krebs cycle was also observed due to phenanthrene exposure. - 1 H NMR metabolomics is used to determine the relationship between phenanthrene exposure and the metabolic response of the earthworm E. fetida over time and also to elucidate the phenanthrene mode of toxicity.

  18. Introducing Undergraduate Students to Metabolomics Using a NMR-Based Analysis of Coffee Beans

    Science.gov (United States)

    Sandusky, Peter Olaf

    2017-01-01

    Metabolomics applies multivariate statistical analysis to sets of high-resolution spectra taken over a population of biologically derived samples. The objective is to distinguish subpopulations within the overall sample population, and possibly also to identify biomarkers. While metabolomics has become part of the standard analytical toolbox in…

  19. Nuclear magnetic resonance-based metabolomics for prediction of gastric damage induced by indomethacin in rats

    Energy Technology Data Exchange (ETDEWEB)

    Um, So Young [Department of Pharmacology, National Institute of Toxicological Research, Korea Food and Drug Administration, 643 Yeonje-ri, Gangoe-myeon, Cheongwon-gun, Chungbuk (Korea, Republic of); Division of Life and Pharmaceutical Science and College of Pharmacy, Ewha Womans University, 52 Ewahyeodae-gil, Seodaemun-gu, Seoul (Korea, Republic of); Park, Jung Hyun [Division of Life and Pharmaceutical Science and College of Pharmacy, Ewha Womans University, 52 Ewahyeodae-gil, Seodaemun-gu, Seoul (Korea, Republic of); Chung, Myeon Woo [Department of Pharmacology, National Institute of Toxicological Research, Korea Food and Drug Administration, 643 Yeonje-ri, Gangoe-myeon, Cheongwon-gun, Chungbuk (Korea, Republic of); Kim, Kyu-Bong [College of Pharmacy, Dankook University, Dandae-ro, Cheonan, Chungnam (Korea, Republic of); Kim, Seon Hwa [Department of Pharmacology, National Institute of Toxicological Research, Korea Food and Drug Administration, 643 Yeonje-ri, Gangoe-myeon, Cheongwon-gun, Chungbuk (Korea, Republic of); Division of Life and Pharmaceutical Science and College of Pharmacy, Ewha Womans University, 52 Ewahyeodae-gil, Seodaemun-gu, Seoul (Korea, Republic of); College of Pharmacy, Dankook University, Dandae-ro, Cheonan, Chungnam (Korea, Republic of); Choi, Ki Hwan, E-mail: hyokwa11@korea.kr [Department of Pharmacology, National Institute of Toxicological Research, Korea Food and Drug Administration, 643 Yeonje-ri, Gangoe-myeon, Cheongwon-gun, Chungbuk (Korea, Republic of); Lee, Hwa Jeong, E-mail: hwalee@ewha.ac.kr [Division of Life and Pharmaceutical Science and College of Pharmacy, Ewha Womans University, 52 Ewahyeodae-gil, Seodaemun-gu, Seoul (Korea, Republic of)

    2012-04-13

    Highlights: Black-Right-Pointing-Pointer NMR based metabolomics - gastric damage by indomethacin. Black-Right-Pointing-Pointer Pattern recognition analysis was performed to biomarkers of gastric damage. Black-Right-Pointing-Pointer 2-Oxoglutarate, acetate, taurine and hippurate were selected as putative biomarkers. Black-Right-Pointing-Pointer The gastric damage induced by NSAIDs can be screened in the preclinical step of drug. - Abstract: Non-steroidal anti-inflammatory drugs (NSAIDs) have side effects including gastric erosions, ulceration and bleeding. In this study, pattern recognition analysis of the {sup 1}H-nuclear magnetic resonance (NMR) spectra of urine was performed to develop surrogate biomarkers related to the gastrointestinal (GI) damage induced by indomethacin in rats. Urine was collected for 5 h after oral administration of indomethacin (25 mg kg{sup -1}) or co-administration with cimetidine (100 mg kg{sup -1}), which protects against GI damage. The {sup 1}H-NMR urine spectra were divided into spectral bins (0.04 ppm) for global profiling, and 36 endogenous metabolites were assigned for targeted profiling. The level of gastric damage in each animal was also determined. Indomethacin caused severe gastric damage; however, indomethacin administered with cimetidine did not. Simultaneously, the patterns of changes in their endogenous metabolites were different. Multivariate data analyses were carried out to recognize the spectral pattern of endogenous metabolites related to indomethacin using partial least square-discrimination analysis. In targeted profiling, a few endogenous metabolites, 2-oxoglutarate, acetate, taurine and hippurate, were selected as putative biomarkers for the gastric damage induced by indomethacin. These metabolites changed depending on the degree of GI damage, although the same dose of indomethacin (10 mg kg{sup -1}) was administered to rats. The results of global and targeted profiling suggest that the gastric damage induced by

  20. Nuclear magnetic resonance-based metabolomics for prediction of gastric damage induced by indomethacin in rats

    International Nuclear Information System (INIS)

    Um, So Young; Park, Jung Hyun; Chung, Myeon Woo; Kim, Kyu-Bong; Kim, Seon Hwa; Choi, Ki Hwan; Lee, Hwa Jeong

    2012-01-01

    Highlights: ► NMR based metabolomics – gastric damage by indomethacin. ► Pattern recognition analysis was performed to biomarkers of gastric damage. ► 2-Oxoglutarate, acetate, taurine and hippurate were selected as putative biomarkers. ► The gastric damage induced by NSAIDs can be screened in the preclinical step of drug. - Abstract: Non-steroidal anti-inflammatory drugs (NSAIDs) have side effects including gastric erosions, ulceration and bleeding. In this study, pattern recognition analysis of the 1 H-nuclear magnetic resonance (NMR) spectra of urine was performed to develop surrogate biomarkers related to the gastrointestinal (GI) damage induced by indomethacin in rats. Urine was collected for 5 h after oral administration of indomethacin (25 mg kg −1 ) or co-administration with cimetidine (100 mg kg −1 ), which protects against GI damage. The 1 H-NMR urine spectra were divided into spectral bins (0.04 ppm) for global profiling, and 36 endogenous metabolites were assigned for targeted profiling. The level of gastric damage in each animal was also determined. Indomethacin caused severe gastric damage; however, indomethacin administered with cimetidine did not. Simultaneously, the patterns of changes in their endogenous metabolites were different. Multivariate data analyses were carried out to recognize the spectral pattern of endogenous metabolites related to indomethacin using partial least square-discrimination analysis. In targeted profiling, a few endogenous metabolites, 2-oxoglutarate, acetate, taurine and hippurate, were selected as putative biomarkers for the gastric damage induced by indomethacin. These metabolites changed depending on the degree of GI damage, although the same dose of indomethacin (10 mg kg −1 ) was administered to rats. The results of global and targeted profiling suggest that the gastric damage induced by NSAIDs can be screened in the preclinical stage of drug development using a NMR based metabolomics approach.

  1. Nutrimetabolomics: An Update on Analytical Approaches to Investigate the Role of Plant-Based Foods and Their Bioactive Compounds in Non-Communicable Chronic Diseases.

    Science.gov (United States)

    Rangel-Huerta, Oscar Daniel; Gil, Angel

    2016-12-09

    Metabolomics is the study of low-weight molecules present in biological samples such as biofluids, tissue/cellular extracts, and culture media. Metabolomics research is increasing, and at the moment, it has several applications in the food science and nutrition fields. In the present review, we provide an update about the most frequently used methodologies and metabolomic platforms in these areas. Also, we discuss different metabolomic strategies regarding the discovery of new bioactive compounds (BACs) in plant-based foods. Furthermore, we review the existing literature related to the use of metabolomics to investigate the potential protective role of BACs in the prevention and treatment of non-communicable chronic diseases, namely cardiovascular disease, diabetes, and cancer.

  2. Nutrimetabolomics: An Update on Analytical Approaches to Investigate the Role of Plant-Based Foods and Their Bioactive Compounds in Non-Communicable Chronic Diseases

    Directory of Open Access Journals (Sweden)

    Oscar Daniel Rangel-Huerta

    2016-12-01

    Full Text Available Metabolomics is the study of low-weight molecules present in biological samples such as biofluids, tissue/cellular extracts, and culture media. Metabolomics research is increasing, and at the moment, it has several applications in the food science and nutrition fields. In the present review, we provide an update about the most frequently used methodologies and metabolomic platforms in these areas. Also, we discuss different metabolomic strategies regarding the discovery of new bioactive compounds (BACs in plant-based foods. Furthermore, we review the existing literature related to the use of metabolomics to investigate the potential protective role of BACs in the prevention and treatment of non-communicable chronic diseases, namely cardiovascular disease, diabetes, and cancer.

  3. Acute psychoactive and toxic effects of D. metel on mice explained by 1H NMR based metabolomics approach.

    Science.gov (United States)

    Fu, Yonghong; Si, Zhihong; Li, Pumin; Li, Minghui; Zhao, He; Jiang, Lei; Xing, Yuexiao; Hong, Wei; Ruan, Lingyu; Wang, Jun-Song

    2017-08-01

    Datura metel L. (D. metel) is one well-known folk medical herb with wide application and also the most abused plants all over the world, mainly for spiritual or religious purpose, over-dosing of which often produces poisonous effects. In this study, mice were orally administered with the extract of D. metel once a day at doses for 10 mg/kg and 40 mg/kg for consecutive 4 days, 1 H NMR based metabolomics approach aided with histopathological inspection and biochemical assays were used for the first time to study the psychoactive and toxic effects of D. metel. Histopathological inspection revealed obvious hypertrophy of hepatocytes, karyolysis and karyorrhexis in livers as well as distinct nerve cell edema, chromatolysis and lower nuclear density in brains. The increased tissue level of methane dicarboxylic aldehyde (MDA) and superoxide dismutase (SOD), decreased tissue level of glutathione (GSH) along with increased serum level of aspartate aminotransferase (AST) and alanine aminotransferase (ALT) suggested brain and liver injury induced by D. metel. Orthogonal signal correction-partial least squares-discriminant analysis (OSC-PLS-DA) of NMR profiles supplemented with correlation network analysis revealed significant altered metabolites and related pathway that contributed to oxidative stress, energy metabolism disturbances, neurotransmitter imbalance and amino acid metabolism disorders.

  4. IDEOM : an Excel interface for analysis of LC-MS-based metabolomics data

    NARCIS (Netherlands)

    Creek, Darren J.; Jankevics, Andris; Burgess, Karl E. V.; Breitling, Rainer; Barrett, Michael P.; Wren, Jonathan

    2012-01-01

    The application of emerging metabolomics technologies to the comprehensive investigation of cellular biochemistry has been limited by bottlenecks in data processing, particularly noise filtering and metabolite identification. IDEOM provides a user-friendly data processing application that automates

  5. Metabolomics Analysis of Effects of Commercial Soy-based Protein Products in Red Drum (Sciaenops ocellatus).

    Science.gov (United States)

    Casu, Fabio; Watson, Aaron M; Yost, Justin; Leffler, John W; Gaylord, Thomas Gibson; Barrows, Frederic T; Sandifer, Paul A; Denson, Michael R; Bearden, Daniel W

    2017-07-07

    We investigated the metabolic effects of four different commercial soy-based protein products on red drum fish (Sciaenops ocellatus) using nuclear magnetic resonance (NMR) spectroscopy-based metabolomics along with unsupervised principal component analysis (PCA) to evaluate metabolic profiles in liver, muscle, and plasma tissues. Specifically, during a 12 week feeding trial, juvenile red drum maintained in an indoor recirculating aquaculture system were fed four different commercially available soy formulations, containing the same amount of crude protein, and two reference diets as performance controls: a 60% soybean meal diet that had been used in a previous trial in our lab and a natural diet. Red drum liver, muscle, and plasma tissues were sampled at multiple time points to provide a more accurate snapshot of specific metabolic states during the grow-out. PCA score plots derived from NMR spectroscopy data sets showed significant differences between fish fed the natural diet and the soy-based diets, in both liver and muscle tissues. While red drum tolerated the inclusion of soy with good feed conversion ratios, a comparison to fish fed the natural diet revealed that the soy-fed fish in this study displayed a distinct metabolic signature characterized by increased protein and lipid catabolism, suggesting an energetic imbalance. Furthermore, among the soy-based formulations, one diet showed a more pronounced catabolic signature.

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

    Science.gov (United States)

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

    2016-01-01

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

  7. Mass Spectrometry-Based Quantitative Metabolomics Revealed a Distinct Lipid Profile in Breast Cancer Patients

    Directory of Open Access Journals (Sweden)

    Yun Yen

    2013-04-01

    Full Text Available Breast cancer accounts for the largest number of newly diagnosed cases in female cancer patients. Although mammography is a powerful screening tool, about 20% of breast cancer cases cannot be detected by this method. New diagnostic biomarkers for breast cancer are necessary. Here, we used a mass spectrometry-based quantitative metabolomics method to analyze plasma samples from 55 breast cancer patients and 25 healthy controls. A number of 30 patients and 20 age-matched healthy controls were used as a training dataset to establish a diagnostic model and to identify potential biomarkers. The remaining samples were used as a validation dataset to evaluate the predictive accuracy for the established model. Distinct separation was obtained from an orthogonal partial least squares-discriminant analysis (OPLS-DA model with good prediction accuracy. Based on this analysis, 39 differentiating metabolites were identified, including significantly lower levels of lysophosphatidylcholines and higher levels of sphingomyelins in the plasma samples obtained from breast cancer patients compared with healthy controls. Using logical regression, a diagnostic equation based on three metabolites (lysoPC a C16:0, PC ae C42:5 and PC aa C34:2 successfully differentiated breast cancer patients from healthy controls, with a sensitivity of 98.1% and a specificity of 96.0%.

  8. Analysis of urinary metabolomic profiling for unstable angina pectoris disease based on nuclear magnetic resonance spectroscopy.

    Science.gov (United States)

    Li, Zhongfeng; Liu, Xinfeng; Wang, Juan; Gao, Jian; Guo, Shuzhen; Gao, Kuo; Man, Hongxue; Wang, Yingfeng; Chen, Jianxin; Wang, Wei

    2015-12-01

    (1)H NMR-based urinary metabolic profiling is used for investigating the unstable angina pectoris (UAP) metabolic signatures, in order to find out candidate biomarkers to facilitate medical diagnosis. In this work, 27 urine samples from UAP patients and 20 healthy controls were used. The metabolic profiles of the samples were analyzed by multivariate statistics analysis, including PCA, PLS-DA and OPLS-DA. The PCA analysis exhibited slight separation with R(2)X of 0.681 and Q2 of 0.251, while the PLS-DA (R(2)X = 0.121, R(2)Y = 0.931, and Q(2) = 0.661) and the OPLS-DA (R(2)X = 0.121, R(2)Y = 0.931, Q(2) = 0.653) demonstrated that the model showed good performance. By OPLS-DA, 20 metabolites were identified. A diagnostic model was further constructed using the receiver-operator characteristic (ROC) curves (AUC = 0.953), which exhibited a satisfying sensitivity of 92.6%, specificity of 90% and accuracy of 89.1%. The results demonstrated that the NMR-based metabolomics approach showed good performance in identifying diagnostic urinary biomarkers, providing new insights into the metabolic process related to UAP.

  9. NMR-based microbial metabolomics and the temperature-dependent coral pathogen Vibrio coralliilyticus.

    Science.gov (United States)

    Boroujerdi, Arezue F B; Vizcaino, Maria I; Meyers, Alexander; Pollock, Elizabeth C; Huynh, Sara Lien; Schock, Tracey B; Morris, Pamela J; Bearden, Daniel W

    2009-10-15

    Coral bleaching occurs when the symbioses between coral animals and their zooxanthellae is disrupted, either as part of a natural cycle or as the result of unusual events. The bacterium Vibrio coralliilyticus (type strain ATCC BAA-450) has been linked to coral disease globally (for example in the Mediterranean, Red Sea, Indian Ocean, and Great Barrier Reef) and like many other Vibrio species exhibits a temperature-dependent pathogenicity. The temperature-dependence of V. corallillyticus in regard to its metabolome was investigated. Nuclear magnetic resonance (NMR) spectra were obtained of methanol-water extracts of intracellula rmetabolites (endometabolome) from multiple samples of the bacteria cultured into late stationary phase at 27 degrees C (virulent form) and 24 degrees C (avirulent form). The spectra were subjected to principal components analysis (PCA), and significant temperature-based separations in PC1, PC2, and PC3 dimensions were observed. Betaine, succinate, and glutamate were identified as metabolites that caused the greatest temperature-based separations in the PC scores plots. With increasing temperature, betaine was shown to be down regulated, while succinate and glutamate were up regulated.

  10. Evaluation of Pacific white shrimp (Litopenaeus vannamei) health during a superintensive aquaculture growout using NMR-based metabolomics.

    Science.gov (United States)

    Schock, Tracey B; Duke, Jessica; Goodson, Abby; Weldon, Daryl; Brunson, Jeff; Leffler, John W; Bearden, Daniel W

    2013-01-01

    Success of the shrimp aquaculture industry requires technological advances that increase production and environmental sustainability. Indoor, superintensive, aquaculture systems are being developed that permit year-round production of farmed shrimp at high densities. These systems are intended to overcome problems of disease susceptibility and of water quality issues from waste products, by operating as essentially closed systems that promote beneficial microbial communities (biofloc). The resulting biofloc can assimilate and detoxify wastes, may provide nutrition for the farmed organisms resulting in improved growth, and may aid in reducing disease initiated from external sources. Nuclear magnetic resonance (NMR)-based metabolomic techniques were used to assess shrimp health during a full growout cycle from the nursery phase through harvest in a minimal-exchange, superintensive, biofloc system. Aberrant shrimp metabolomes were detected from a spike in total ammonia nitrogen in the nursery, from a reduced feeding period that was a consequence of surface scum build-up in the raceway, and from the stocking transition from the nursery to the growout raceway. The biochemical changes in the shrimp that were induced by the stressors were essential for survival and included nitrogen detoxification and energy conservation mechanisms. Inosine and trehalose may be general biomarkers of stress in Litopenaeus vannamei. This study demonstrates one aspect of the practicality of using NMR-based metabolomics to enhance the aquaculture industry by providing physiological insight into common environmental stresses that may limit growth or better explain reduced survival and production.

  11. Evaluation of Pacific white shrimp (Litopenaeus vannamei health during a superintensive aquaculture growout using NMR-based metabolomics.

    Directory of Open Access Journals (Sweden)

    Tracey B Schock

    Full Text Available Success of the shrimp aquaculture industry requires technological advances that increase production and environmental sustainability. Indoor, superintensive, aquaculture systems are being developed that permit year-round production of farmed shrimp at high densities. These systems are intended to overcome problems of disease susceptibility and of water quality issues from waste products, by operating as essentially closed systems that promote beneficial microbial communities (biofloc. The resulting biofloc can assimilate and detoxify wastes, may provide nutrition for the farmed organisms resulting in improved growth, and may aid in reducing disease initiated from external sources. Nuclear magnetic resonance (NMR-based metabolomic techniques were used to assess shrimp health during a full growout cycle from the nursery phase through harvest in a minimal-exchange, superintensive, biofloc system. Aberrant shrimp metabolomes were detected from a spike in total ammonia nitrogen in the nursery, from a reduced feeding period that was a consequence of surface scum build-up in the raceway, and from the stocking transition from the nursery to the growout raceway. The biochemical changes in the shrimp that were induced by the stressors were essential for survival and included nitrogen detoxification and energy conservation mechanisms. Inosine and trehalose may be general biomarkers of stress in Litopenaeus vannamei. This study demonstrates one aspect of the practicality of using NMR-based metabolomics to enhance the aquaculture industry by providing physiological insight into common environmental stresses that may limit growth or better explain reduced survival and production.

  12. Evaluation of Pacific White Shrimp (Litopenaeus vannamei) Health during a Superintensive Aquaculture Growout Using NMR-Based Metabolomics

    Science.gov (United States)

    Schock, Tracey B.; Duke, Jessica; Goodson, Abby; Weldon, Daryl; Brunson, Jeff; Leffler, John W.; Bearden, Daniel W.

    2013-01-01

    Success of the shrimp aquaculture industry requires technological advances that increase production and environmental sustainability. Indoor, superintensive, aquaculture systems are being developed that permit year-round production of farmed shrimp at high densities. These systems are intended to overcome problems of disease susceptibility and of water quality issues from waste products, by operating as essentially closed systems that promote beneficial microbial communities (biofloc). The resulting biofloc can assimilate and detoxify wastes, may provide nutrition for the farmed organisms resulting in improved growth, and may aid in reducing disease initiated from external sources. Nuclear magnetic resonance (NMR)-based metabolomic techniques were used to assess shrimp health during a full growout cycle from the nursery phase through harvest in a minimal-exchange, superintensive, biofloc system. Aberrant shrimp metabolomes were detected from a spike in total ammonia nitrogen in the nursery, from a reduced feeding period that was a consequence of surface scum build-up in the raceway, and from the stocking transition from the nursery to the growout raceway. The biochemical changes in the shrimp that were induced by the stressors were essential for survival and included nitrogen detoxification and energy conservation mechanisms. Inosine and trehalose may be general biomarkers of stress in Litopenaeus vannamei. This study demonstrates one aspect of the practicality of using NMR-based metabolomics to enhance the aquaculture industry by providing physiological insight into common environmental stresses that may limit growth or better explain reduced survival and production. PMID:23555690

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

    Science.gov (United States)

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

    2015-11-01

    ), which showed that phenylacetic acid may be used as a reliable discriminator for the diagnosis of PKU. The low false positive rate (1-specificity, 0.064) can be eliminated or at least greatly reduced by simultaneously referring to other markers, especially phenylpyruvic acid, a unique marker in PKU. Additionally, this standard was obtained with high sensitivity and specificity in a less invasive manner for diagnosing PKU compared with the Phe/Tyr ratio. Therefore, we conclude that urinary metabolomic information based on the improved oximation-silylation method together with GC/MS may be reliable for the diagnosis and differential diagnosis of PKU.

  14. Biochemical disorders induced by cytotoxic marine natural products in breast cancer cells as revealed by proton NMR spectroscopy-based metabolomics.

    Science.gov (United States)

    Bayet-Robert, Mathilde; Lim, Suzanne; Barthomeuf, Chantal; Morvan, Daniel

    2010-10-15

    Marine plants and animals are sources of a huge number of pharmacologically active compounds, some of which exhibit antineoplastic activity of clinical relevance. However the mechanism of action of marine natural products (MNPs) is poorly understood. In this study, proton NMR spectroscopy-based metabolomics was applied to unravel biochemical disorders induced in human MCF7 breast cancer cells by 3 lead candidate anticancer MNPs: ascididemin (Asc), lamellarin-D (Lam-D), and kahalalide F (KF). Asc, Lam-D, and KF provoked a severe decrease in DNA content in MCF7 cells after 24-h treatment. Asc and Lam-D provoked apoptosis, whereas KF induced non-apoptotic cell death. Metabolite profiling revealed major biochemical disorders following treatment. The response of MCF7 tumor cells to Asc involved the accumulation of citrate (x17 the control level, Pmechanism of cytotoxicity of candidate antineoplastic MNPs. Copyright 2010 Elsevier Inc. All rights reserved.

  15. Metabolomics in Immunology Research.

    Science.gov (United States)

    Everts, Bart

    2018-01-01

    There is a growing appreciation that metabolic processes and individual metabolites can shape the function of immune cells and thereby play important roles in the outcome of immune responses. In this respect, the use of MS- and NMR spectroscopy-based platforms to characterize and quantify metabolites in biological samples has recently yielded important novel insights into how our immune system functions and has contributed to the identification of biomarkers for immune-mediated diseases. Here, these recent immunological studies in which metabolomics has been used and made significant contributions to these fields will be discussed. In particular the role of metabolomics to the rapidly advancing field of cellular immunometabolism will be highlighted as well as the future prospects of such metabolomic tools in immunology.

  16. A GC-MS based metabolomics approach to determine the effect of salinity on Kimchi.

    Science.gov (United States)

    Seo, Seung-Ho; Park, Seong-Eun; Kim, Eun-Ju; Lee, Kyoung-In; Na, Chang-Su; Son, Hong-Seok

    2018-03-01

    GC-MS datasets coupled with multivariate statistical analysis were used to investigate metabolic changes in Kimchi during fermentation and metabolic differences in Kimchi added with various amounts (0, 1.25, 2.5, and 5%) of salts. PCA score plot obtained after 1day of fermentation were clearly distinguishable by different salinity groups, implying that early fermentation speed varied according to Kimchi salinity. PLS-DA score plot from data obtained on the 50th day of fermentation also showed a clear separation, indicating metabolites of Kimchi were different according to salinity. Concentrations of lactic acid, acetic acid, and xylitol were the highest in Kimchi with 5% salinity while concentration of fumaric acid was the highest in Kimchi with 0% salinity. Rarefaction curves showed that numbers of operational taxonomic units (OTUs) in Kimchi with 5% salinity were higher than those in Kimchi with 0% salinity, implying that Kimchi with 5% salinity had more bacterial diversities. This study highlights the applicability of GC-MS based metabolomics for evaluating fermentative characteristics of Kimchi with different salinities. Copyright © 2017 Elsevier Ltd. All rights reserved.

  17. [Monitoring of chemical components with different color traits of Tussilago farfara using NMR-based metabolomics].

    Science.gov (United States)

    Mi, Xi; Li, Zhen-yu; Qin, Xue-mei; Zhang, Li-zeng

    2013-11-01

    The quality and grade of traditional Chinese medicinal herbs were assessed by their characteristics traditionally. According to traditional experience, the quality of the purple Flos Farfarae is better than that of yellow buds. NMR-based metabolomic approach combined with significant analysis of microarray (SAM) and Spearman rank correlation analysis were used to investigate the different metabolites of the Flos Farfarae with different color feature. Principal component analysis (PCA) showed clear distinction between the purple and yellow flower buds of Tussilago farfara. The S-plot of orthogonal PLS-DA (OPLS-DA) and t test revealed that the levels of threonine, proline, phosphatidylcholine, creatinine, 4, 5-dicaffeoylquinic acid, rutin, caffeic acid, kaempferol analogues, and tussilagone were higher in the purple flower buds than that in the yellow buds, in agreement with the results of SAM and Spearman rank correlation analysis. The results confirmed the traditional medication experience that "purple flower bud is better than the yellow ones", and provide a scientific basis for assessing the quality of Flos Farfarae by the color features.

  18. Application of (1)H NMR-based serum metabolomic studies for monitoring female patients with rheumatoid arthritis.

    Science.gov (United States)

    Zabek, Adam; Swierkot, Jerzy; Malak, Anna; Zawadzka, Iga; Deja, Stanisław; Bogunia-Kubik, Katarzyna; Mlynarz, Piotr

    2016-01-05

    Rheumatoid arthritis is a chronic autoimmune-based inflammatory disease that leads to progressive joint degeneration, disability, and an increased risk of cardiovascular complications, which is the main cause of mortality in this population of patients. Although several biomarkers are routinely used in the management of rheumatoid arthritis, there is a high demand for novel biomarkers to further improve the early diagnosis of rheumatoid arthritis, stratification of patients, and the prediction of a better response to a specific therapy. In this study, the metabolomics approach was used to provide relevant biomarkers to improve diagnostic accuracy, define prognosis and predict and monitor treatment efficacy. The results indicated that twelve metabolites were important for the discrimination of healthy control and rheumatoid arthritis. Notably, valine, isoleucine, lactate, alanine, creatinine, GPC  APC and histidine relative levels were lower in rheumatoid arthritis, whereas 3-hydroxyisobutyrate, acetate, NAC, acetoacetate and acetone relative levels were higher. Simultaneously, the analysis of the concentration of metabolites in rheumatoid arthritis and 3 months after induction treatment revealed that L1, 3-hydroxyisobutyrate, lysine, L5, acetoacetate, creatine, GPC+APC, histidine and phenylalanine were elevated in RA, whereas leucine, acetate, betaine and formate were lower. Additionally, metabolomics tools were employed to discriminate between patients with different IL-17A genotypes. Metabolomics may provide relevant biomarkers to improve diagnostic accuracy, define prognosis and predict and monitor treatment efficacy in rheumatoid arthritis. Copyright © 2015 The Authors. Published by Elsevier B.V. All rights reserved.

  19. Stress-inducible GmGSTU4 shapes transgenic tobacco plants metabolome towards increased salinity tolerance

    NARCIS (Netherlands)

    Kissoudis, Christos; Kalloniati, Chrissanthi; Flemetakis, Emmanouil; Madesis, Panagiotis; Labrou, Nikolaos E.; Tsaftaris, Athanasios; Nianiou-Obeidat, Irini

    2015-01-01

    The involvement of glutathione transferases (GSTs) in plant’s tolerance to abiotic stresses has been extensively studied; however, the metabolic changes occurring in the plants with altered GSTs expression have not been studied in detail. We have previously demonstrated that GmGSTU4

  20. Comparison of Fruits of Forsythia suspensa at Two Different Maturation Stages by NMR-Based Metabolomics

    Directory of Open Access Journals (Sweden)

    Jinping Jia

    2015-05-01

    Full Text Available Forsythiae Fructus (FF, the dried fruit of Forsythia suspensa, has been widely used as a heat-clearing and detoxifying herbal medicine in China. Green FF (GF and ripe FF (RF are fruits of Forsythia suspensa at different maturity stages collected about a month apart. FF undergoes a complex series of physical and biochemical changes during fruit ripening. However, the clinical uses of GF and RF have not been distinguished to date. In order to comprehensively compare the chemical compositions of GF and RF, NMR-based metabolomics coupled with HPLC and UV spectrophotometry methods were adopted in this study. Furthermore, the in vitro antioxidant and antibacterial activities of 50% methanol extracts of GF and RF were also evaluated. A total of 27 metabolites were identified based on NMR data, and eight of them were found to be different between the GF and RF groups. The GF group contained higher levels of forsythoside A, forsythoside C, cornoside, rutin, phillyrin and gallic acid and lower levels of rengyol and β-glucose compared with the RF group. The antioxidant activity of GF was higher than that of RF, but no significant difference was observed between the antibacterial activities of GF and RF. Given our results showing their distinct chemical compositions, we propose that NMR-based metabolic profiling can be used to discriminate between GF and RF. Differences in the chemical and biological activities of GF and RF, as well as their clinical efficacies in traditional Chinese medicine should be systematically investigated in future studies.

  1. Evaluation of the anti-hypertensive effect of Tengfu Jiangya tablet by combination of UPLC-Q-exactive-MS-based metabolomics and iTRAQ-based proteomics technology.

    Science.gov (United States)

    Tian, Yanpeng; Jiang, Feng; Li, Yunlun; Jiang, Haiqiang; Chu, Yanjun; Zhu, Lijuan; Guo, Weixing

    2018-04-01

    Tengfu Jiangya tablet (TJT) is a traditional Chinese medicine formulation composed of Uncaria rhynchophylla and Semen raphani. It is a hospital preparation that is widely used in clinics for treating hypertension. A previous metabolomics study reported that TJT exerted a protective effect on hypertension by restoring impaired NO production, ameliorating the inflammatory state, and vascular remodeling. A clinical proteomics study also revealed five key target proteins during TJT intervention. This study aimed to integrate proteome and metabolome data sets for a holistic view of the molecular mechanisms of TJT in treating hypertension. Serum samples from spontaneously hypertensive rats and Wistar Kyoto rats were analyzed using ultra-high performance liquid chromatography coupled to Q Exactive hybrid quadrupole-Orbitrap mass spectrometry (UPLC-Q-Exactive-MS)-based metabolomics technology and isobaric tags for relative and absolute quantitation (iTRAQ)-based quantitative proteomics technology. Moreover, we selected two candidate proteins and determined their expression levels in rat serum using an enzyme-linked immunosorbent assay (ELISA). A total of 20 potential biomarkers and 14 differential proteins in rat serum were identified. These substances were mainly involved in three biological pathways: the kallikrein-kinin pathway, the lipid metabolism pathway, and the PPARγ signaling pathway. The results suggested that TJT could effectively treat hypertension, partially by regulating the above three metabolic pathways. The combination of proteomics and metabolomics provided a feasible method to uncover the underlying interventional effect and therapeutic mechanism of TJT on spontaneously hypertensive rats. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

  2. Heavy Metal Tolerance in Plants: Role of Transcriptomics, Proteomics, Metabolomics, and Ionomics

    OpenAIRE

    Singh, Samiksha; Parihar, Parul; Singh, Rachana; Singh, Vijay P.; Prasad, Sheo M.

    2016-01-01

    Heavy metal contamination of soil and water causing toxicity/stress has become one important constraint to crop productivity and quality. This situation has further worsened by the increasing population growth and inherent food demand. It has been reported in several studies that counterbalancing toxicity due to heavy metal requires complex mechanisms at molecular, biochemical, physiological, cellular, tissue, and whole plant level, which might manifest in terms of improved crop productivity....

  3. Application of a Smartphone Metabolomics Platform to the Authentication of Schisandra sinensis.

    Science.gov (United States)

    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.

  4. (13)C NMR-based metabolomics for the classification of green coffee beans according to variety and origin.

    Science.gov (United States)

    Wei, Feifei; Furihata, Kazuo; Koda, Masanori; Hu, Fangyu; Kato, Rieko; Miyakawa, Takuya; Tanokura, Masaru

    2012-10-10

    (13)C NMR-based metabolomics was demonstrated as a useful tool for distinguishing the species and origins of green coffee bean samples of arabica and robusta from six different geographic regions. By the application of information on (13)C signal assignment, significantly different levels of 14 metabolites of green coffee beans were identified in the classifications, including sucrose, caffeine, chlorogenic acids, choline, amino acids, organic acids, and trigonelline, as captured by multivariate analytical models. These studies demonstrate that the species and geographical origin can be quickly discriminated by evaluating the major metabolites of green coffee beans quantitatively using (13)C NMR-based metabolite profiling.

  5. Metabolomics of Genetically Modified Crops

    Directory of Open Access Journals (Sweden)

    Carolina Simó

    2014-10-01

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

  6. Metabolomics of genetically modified crops.

    Science.gov (United States)

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

    2014-10-20

    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.

  7. Metabolomics of Genetically Modified Crops

    Science.gov (United States)

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

    2014-01-01

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

  8. Clinical validation of a novel urine-based metabolomic test for the detection of colonic polyps on Chinese population.

    Science.gov (United States)

    Deng, Lu; Fang, Hong; Tso, Victor K; Sun, Yuanyuan; Foshaug, Rae R; Krahn, Spencer C; Zhang, Fen; Yan, Yujie; Xu, Huilin; Chang, David; Zhang, Yong; Fedorak, Richard N

    2017-05-01

    Colorectal cancer is the fifth leading cause of cancer-related deaths in China. When detected early, with the removal of adenomatous polyps, precursors of colorectal cancer, it is preventable. The aim of this study was to evaluate a novel urine-based metabolomic diagnostic test for the detection of adenomatous polyps, PolypDx™, that was originally developed and validated using 1000 samples from Canadian Cohort, on Chinese population. Prospective urine samples were collected from 1000 participants undergoing colonoscopy examination, from March 2013 to July 2014 at Minhang District, Shanghai Centre for Disease Control and Prevention. One-dimensional nuclear magnetic resonance spectra of urine metabolites were analyzed to determine the concentrations of three key metabolites used in PolypDx™. The predicted results were then compared to the gold standard for colorectal cancer diagnostic, colonoscopy. Area under curve (AUC) was calculated specifically for the Chinese population and compared with the Canadian dataset. Sensitivity and specificity of this urine-based metabolomic diagnostic test were also compared with three commercially available fecal-based tests. An AUC of 0.717 for PolypDx™ was calculated on Chinese dataset which is slightly lower than the AUC on the Canadian dataset. A sensitivity of 82.6% and a specificity of 42.4% were achieved on Chinese dataset. Here, we validated a novel urine-based metabolomic diagnostic test for the detection of adenomatous polyps, PolypDx™, on Chinese population through a sample size of 1000 participants with a greater level of sensitivity than fecal-based tests.

  9. Can NMR solve some significant challenges in metabolomics?

    Science.gov (United States)

    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.

  10. Assessment of clam ruditapes philippinarum as Heavy metal bioindicators using NMR-based metabolomics

    Energy Technology Data Exchange (ETDEWEB)

    Liu, Xiaoli; Zhang, Linbao; You, Liping [Key Laboratory of Coastal Zone Environment Processes, CAS, Shandong Provincial Key Laboratory of Coastal Zone Environment Processes, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai (China); The Graduate School of Chinese Academy of Sciences, Beijing (China); Yu, Junbao; Cong, Ming; Wang, Qing; Li, Fei; Li, Lianzhen; Zhao, Jianmin; Li, Chenghua; Wu, Huifeng [Key Laboratory of Coastal Zone Environment Processes, CAS, Shandong Provincial Key Laboratory of Coastal Zone Environment Processes, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai (China)

    2011-08-15

    There are mainly distributed three pedigrees (White, Liangdao Red, and Zebra) of Manila clam Ruditapes philippinarum in Yantai population along the Bohai marine and coast. However, the biological differences to environmental stressors have been ignored in toxicology studies, which could lead to the distortion of biological interpretations of toxicological effects induced by environmental contaminants. In this study, we applied a system biology approach, metabolomics to compare the metabolic profiles in digestive gland from three pedigrees of clam and characterize and compare the metabolic responses induced by mercury in clam digestive gland tissues to determine a sensitive pedigree of clam as a preferable bioindicator for metal pollution monitoring and toxicology research. The most abundant metabolites, respectively, included branched-chain amino acids, alanine, and arginine in White samples, glutamate, dimethylglycine, and glycine in Zebra clams and acetylcholine, betaine, glucose, and glycogen in Liangdao Red clams. After 48 h exposure of 20 {mu}g L{sup -1} Hg{sup 2+}, the metabolic profiles from the three pedigrees of clams showed differentially significant changes in alanine, glutamate, succinate, taurine, hypotaurine, glycine, arginine, glucose, etc. Our findings indicate the toxicological effects of mercury exposure in Manila clams including the neurotoxicity, disturbances in energetic metabolisms and osmoregulation in the digestive glands and suggest that Liangdao Red pedigree of clam could be a preferable bioindicator for the metal pollution monitoring based on the more sensitive classes of metabolic changes from digestive glands compared with other two (White and Zebra) pedigrees of clams. (Copyright copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  11. 1H NMR- based metabolomics approaches as non- invasive tools for diagnosis of endometriosis

    Directory of Open Access Journals (Sweden)

    Negar Ghazi

    2016-01-01

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

  12. LC-MS Based Serum Metabolomics for Identification of Hepatocellular Carcinoma Biomarkers in Egyptian Cohort

    Science.gov (United States)

    Xiao, Jun Feng; Varghese, Rency S.; Zhou, Bin; Nezami Ranjbar, Mohammad R.; Zhao, Yi; Tsai, Tsung-Heng; Di Poto, Cristina; Wang, Jinlian; Goerlitz, David; Luo, Yue; Cheema, Amrita K.; Sarhan, Naglaa; Soliman, Hanan; Tadesse, Mahlet G.; Ziada, Dina Hazem; Ressom, Habtom W.

    2013-01-01

    confirmed significant differences between HCC and cirrhotic controls in metabolite levels of bile acid metabolites, long chain carnitines and small peptide. Our study provides useful insight into appropriate experimental design and computational methods for serum biomarker discovery using LC-MS/MS based metabolomics. This study has led to the identification of candidate biomarkers with significant changes in metabolite levels between HCC cases and cirrhotic controls. This is the first MS-based metabolic biomarker discovery study on Egyptian subjects that led to the identification of candidate metabolites that discriminate early stage HCC from patients with liver cirrhosis. PMID:23078175

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

    Science.gov (United States)

    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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2014-01-15

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

  15. Application of NMR-based metabolomics for environmental assessment in the Great Lakes using zebra mussel (Dreissena polymorpha).

    Science.gov (United States)

    Watanabe, Miki; Meyer, Kathryn A; Jackson, Tyler M; Schock, Tracey B; Johnson, W Edward; Bearden, Daniel W

    Zebra mussel, Dreissena polymorpha , in the Great Lakes is being monitored as a bio-indicator organism for environmental health effects by the National Oceanic and Atmospheric Administration's Mussel Watch program. In order to monitor the environmental effects of industrial pollution on the ecosystem, invasive zebra mussels were collected from four stations-three inner harbor sites (LMMB4, LMMB1, and LMMB) in Milwaukee Estuary, and one reference site (LMMB5) in Lake Michigan, Wisconsin. Nuclear magnetic resonance (NMR)-based metabolomics was used to evaluate the metabolic profiles of the mussels from these four sites. The objective was to observe whether there were differences in metabolite profiles between impacted sites and the reference site; and if there were metabolic profile differences among the impacted sites. Principal component analyses indicated there was no significant difference between two impacted sites: north Milwaukee harbor (LMMB and LMMB4) and the LMMB5 reference site. However, significant metabolic differences were observed between the impacted site on the south Milwaukee harbor (LMMB1) and the LMMB5 reference site, a finding that correlates with preliminary sediment toxicity results. A total of 26 altered metabolites (including two unidentified peaks) were successfully identified in a comparison of zebra mussels from the LMMB1 site and LMMB5 reference site. The application of both uni- and multivariate analysis not only confirmed the variability of altered metabolites but also ensured that these metabolites were identified via unbiased analysis. This study has demonstrated the feasibility of the NMR-based metabolomics approach to assess whole-body metabolomics of zebra mussels to study the physiological impact of toxicant exposure at field sites.

  16. Nutritional Metabolomics

    DEFF Research Database (Denmark)

    Gürdeniz, Gözde

    Metabolomics provides a holistic approach to investigate the perturbations in human metabolism with respect to a specific exposure. In nutritional metabolomics, the research question is generally related to the effect of a specific food intake on metabolic profiles commonly of plasma or urine...... strategy influences the patterns identified as important for the nutritional question under study. Therefore, in depth understanding of the study design and the specific effects of the analytical technology on the produced data is extremely important to achieve high quality data handling. Besides data...... handling, this thesis also deals with biological interpretation of postprandial metabolism and trans fatty acid (TFA) intake. Two nutritional issues were objects of investigation: 1) metabolic states as a function of time since the last meal and 2) markers related to intakes of cis- and trans-fat. Plasma...

  17. Mass spectra-based framework for automated structural elucidation of metabolome data to explore phytochemical diversity

    Directory of Open Access Journals (Sweden)

    Fumio eMatsuda

    2011-08-01

    Full Text Available A novel framework for automated elucidation of metabolite structures in liquid chromatography-mass spectrometer (LC-MS metabolome data was constructed by integrating databases. High-resolution tandem mass spectra data automatically acquired from each metabolite signal were used for database searches. Three distinct databases, KNApSAcK, ReSpect, and the PRIMe standard compound database, were employed for the structural elucidation. The outputs were retrieved using the CAS metabolite identifier for identification and putative annotation. A simple metabolite ontology system was also introduced to attain putative characterization of the metabolite signals. The automated method was applied for the metabolome data sets obtained from the rosette leaves of 20 Arabidopsis accessions. Phenotypic variations in novel Arabidopsis metabolites among these accessions could be investigated using this method.

  18. Metabolic Model-Based Integration of Microbiome Taxonomic and Metabolomic Profiles Elucidates Mechanistic Links between Ecological and Metabolic Variation

    Energy Technology Data Exchange (ETDEWEB)

    Noecker, Cecilia; Eng, Alexander; Srinivasan, Sujatha; Theriot, Casey M.; Young, Vincent B.; Jansson, Janet K.; Fredricks, David N.; Borenstein, Elhanan; Sanchez, Laura M.

    2015-12-22

    health and disease.

    IMPORTANCEStudies characterizing both the taxonomic composition and metabolic profile of various microbial communities are becoming increasingly common, yet new computational methods are needed to integrate and interpret these data in terms of known biological mechanisms. Here, we introduce an analytical framework to link species composition and metabolite measurements, using a simple model to predict the effects of community ecology on metabolite concentrations and evaluating whether these predictions agree with measured metabolomic profiles. We find that a surprisingly large proportion of metabolite variation in the vaginal microbiome can be predicted based on species composition (including dramatic shifts associated with disease), identify putative mechanisms underlying these predictions, and evaluate the roles of individual bacterial species and genes. Analysis of gut microbiome data using this framework recovers similar community metabolic trends. This framework lays the foundation for model-based multi-omic integrative studies, ultimately improving our understanding of microbial community metabolism.

  19. Mass spectrometry-based metabolomic fingerprinting for screening cold tolerance in Arabidopsis thaliana accessions

    Czech Academy of Sciences Publication Activity Database

    Václavík, L.; Mishra, Anamika; Mishra, Kumud; Hajslova, J.

    2013-01-01

    Roč. 405, č. 8 (2013), s. 2671-2683 ISSN 1618-2642 R&D Projects: GA MŠk(CZ) ED1.1.00/02.0073; GA MŠk OC08055 Institutional support: RVO:67179843 Keywords : cold tolerance * Arabidopsis thaliana * metabolomic fingerprinting * LC-MS * DART-MS * chemometric analysis Subject RIV: EH - Ecology, Behaviour Impact factor: 3.578, year: 2013

  20. MSPrep--summarization, normalization and diagnostics for processing of mass spectrometry-based metabolomic data.

    Science.gov (United States)

    Hughes, Grant; Cruickshank-Quinn, Charmion; Reisdorph, Richard; Lutz, Sharon; Petrache, Irina; Reisdorph, Nichole; Bowler, Russell; Kechris, Katerina

    2014-01-01

    Although R packages exist for the pre-processing of metabolomic data, they currently do not incorporate additional analysis steps of summarization, filtering and normalization of aligned data. We developed the MSPrep R package to complement other packages by providing these additional steps, implementing a selection of popular normalization algorithms and generating diagnostics to help guide investigators in their analyses. http://www.sourceforge.net/projects/msprep

  1. MASTR-MS: a web-based collaborative laboratory information management system (LIMS) for metabolomics.

    Science.gov (United States)

    Hunter, Adam; Dayalan, Saravanan; De Souza, David; Power, Brad; Lorrimar, Rodney; Szabo, Tamas; Nguyen, Thu; O'Callaghan, Sean; Hack, Jeremy; Pyke, James; Nahid, Amsha; Barrero, Roberto; Roessner, Ute; Likic, Vladimir; Tull, Dedreia; Bacic, Antony; McConville, Malcolm; Bellgard, Matthew

    2017-01-01

    An increasing number of research laboratories and core analytical facilities around the world are developing high throughput metabolomic analytical and data processing pipelines that are capable of handling hundreds to thousands of individual samples per year, often over multiple projects, collaborations and sample types. At present, there are no Laboratory Information Management Systems (LIMS) that are specifically tailored for metabolomics laboratories that are capable of tracking samples and associated metadata from the beginning to the end of an experiment, including data processing and archiving, and which are also suitable for use in large institutional core facilities or multi-laboratory consortia as well as single laboratory environments. Here we present MASTR-MS, a downloadable and installable LIMS solution that can be deployed either within a single laboratory or used to link workflows across a multisite network. It comprises a Node Management System that can be used to link and manage projects across one or multiple collaborating laboratories; a User Management System which defines different user groups and privileges of users; a Quote Management System where client quotes are managed; a Project Management System in which metadata is stored and all aspects of project management, including experimental setup, sample tracking and instrument analysis, are defined, and a Data Management System that allows the automatic capture and storage of raw and processed data from the analytical instruments to the LIMS. MASTR-MS is a comprehensive LIMS solution specifically designed for metabolomics. It captures the entire lifecycle of a sample starting from project and experiment design to sample analysis, data capture and storage. It acts as an electronic notebook, facilitating project management within a single laboratory or a multi-node collaborative environment. This software is being developed in close consultation with members of the metabolomics research

  2. Liquid chromatography time of flight mass spectrometry based environmental metabolomics for the analysis of Pseudomonas putida Bacteria in potable water.

    Science.gov (United States)

    Kouremenos, Konstantinos A; Beale, David J; Antti, Henrik; Palombo, Enzo A

    2014-09-01

    Water supply biofilms have the potential to harbour waterborne diseases, accelerate corrosion, and contribute to the formation of tuberculation in metallic pipes. One particular species of bacteria known to be found in the water supply networks is Pseudomonas sp., with the presence of Pseudomonas putida being isolated to iron pipe tubercles. Current methods for detecting and analysis pipe biofilms are time consuming and expensive. The application of metabolomics techniques could provide an alternative method for assessing biofilm risk more efficiently based on bacterial activity. As such, this paper investigates the application of metabolomic techniques and provides a proof-of-concept application using liquid chromatography coupled with time-of-flight mass spectrometry (LC-ToF-MS) to three biologically independent P. putida samples, across five different growth conditions exposed to solid and soluble iron (Fe). Analysis of the samples in +ESI and -ESI mode yielded 887 and 1789 metabolite features, respectively. Chemometric analysis of the +ESI and -ESI data identified 34 and 39 significant metabolite features, respectively, where features were considered significant if the fold change was greater than 2 and obtained a p-value less than 0.05. Metabolite features were subsequently identified according to the Metabolomics Standard Initiative (MSI) Chemical Analysis Workgroup using analytical standards and standard online LC-MS databases. Possible markers for P. putida growth, with and without being exposed to solid and soluble Fe, were identified from a diverse range of different chemical classes of metabolites including nucleobases, nucleosides, dipeptides, tripeptides, amino acids, fatty acids, sugars, and phospholipids. Copyright © 2014 Elsevier B.V. All rights reserved.

  3. Recommendations and Standardization of Biomarker Quantification Using NMR-Based Metabolomics with Particular Focus on Urinary Analysis.

    Science.gov (United States)

    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.

  4. A UPLC-TOF/MS-based metabolomics study of rattan stems of Schisandra chinensis effects on Alzheimer's disease rats model.

    Science.gov (United States)

    Yang, Bing-You; Tan, Jin-Yan; Liu, Yan; Liu, Bo; Jin, Shuang; Guo, Hong-Wei; Kuang, Hai-Xue

    2018-02-01

    A UPLC-TOF/MS-based metabolomics method was established to explore the therapeutic mechanisms of rattan stems of S. chinensis (SCS) in Alzheimer's disease (AD). Experimental AD model was induced by intra-hippocampal Aβ 1-42 injection in rats. Cognitive function and oxidative stress condition in brain of AD rats were assessed using Morris water maze tests and antioxidant assays [malondialdehyde (MDA), superoxide dismutase (SOD) and glutathione peroxidase (GSH-Px)], respectively. UPLC-TOF/MS combined with multivariate statistical analysis were conducted to study the changes in metabolic networks in serum of rats. The results indicated that the AD model was established successfully and the inducement of Aβ 1-42 caused a decline in spatial learning and memory of rats. The injection of Aβ 1-42 in rat brains significantly elevated the level of MDA, and reduced SOD and GSH-Px activities. In addition, SCS showed significant anti-AD effects on model rats. A total of 30 metabolites were finally identified as potential biomarkers of AD and 14 of them had a significant recovery compared with the AD model after SCS administration. Changes in AD metabolite profiling were restored to different levels through the regulation of 13 pathways. This is first report on the use of the UPLC-TOF/MS-based serum metabolomics method to investigate therapeutic effects of SCS on AD, and enrich potential biomarkers and metabolic networks of AD. Copyright © 2017 John Wiley & Sons, Ltd.

  5. Recommendations and Standardization of Biomarker Quantification Using NMR-based Metabolomics with Particular Focus on Urinary Analysis

    KAUST Repository

    Emwas, Abdul-Hamid M.

    2016-01-08

    NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to non-destructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Indeed, precise metabolite quantification is a necessary prerequisite to move any chemical biomarker or biomarker panel from the lab into the clinic. Among the many biofluids (urine, serum, plasma, cerebrospinal fluid and saliva) commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, easily obtained, needs little sample preparation and does not require any invasive medical procedures for collection. Furthermore, urine captures and concentrates many “unwanted” or “undesirable” compounds throughout the body, thereby providing a rich source of potentially useful disease biomarkers. However, the incredible variation in urine chemical concentrations due to effects such as gender, age, diet, life style, health conditions, and physical activity make the analysis of urine and the identification of useful urinary biomarkers by NMR quite challenging. In this review, we discuss a number of the most significant issues regarding NMR-based urinary metabolomics with a specific emphasis on metabolite quantification for disease biomarker applications. We also propose a number of data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, as well as recommendations regarding sample preparation and biomarker assessment.

  6. (1)H NMR-based metabolomics of Daphnia magna responses after sub-lethal exposure to triclosan, carbamazepine and ibuprofen.

    Science.gov (United States)

    Kovacevic, Vera; Simpson, André J; Simpson, Myrna J

    2016-09-01

    Pharmaceuticals and personal care products are a class of emerging contaminants that are present in wastewater effluents, surface water, and groundwater around the world. There is a need to determine rapid and reliable bioindicators of exposure and the toxic mode of action of these contaminants to aquatic organisms. (1)H nuclear magnetic resonance (NMR)-based metabolomics in combination with multivariate statistical analysis was used to determine the metabolic profile of Daphnia magna after exposure to a range of sub-lethal concentrations of triclosan (6.25-100μg/L), carbamazepine (1.75-14mg/L) and ibuprofen (1.75-14mg/L) for 48h. Sub-lethal triclosan exposure suggested a general oxidative stress condition and the branched-chain amino acids, glutamine, glutamate, and methionine emerged as potential bioindicators. The aromatic amino acids, serine, glycine and alanine are potential bioindicators for sub-lethal carbamazepine exposure that may have altered energy metabolism. The potential bioindicators for sub-lethal ibuprofen exposure are serine, methionine, lysine, arginine and leucine, which showed a concentration-dependent response. The differences in the metabolic changes were related to the dissimilar modes of toxicity of triclosan, carbamazepine and ibuprofen. (1)H NMR-based metabolomics gave an improved understanding of how these emerging contaminants impact the keystone species D. magna. Copyright © 2016 Elsevier Inc. All rights reserved.

  7. The co-feature ratio, a novel method for the measurement of chromatographic and signal selectivity in LC-MS-based metabolomics

    Energy Technology Data Exchange (ETDEWEB)

    Elmsjö, Albert, E-mail: Albert.Elmsjo@farmkemi.uu.se [Department of Medicinal Chemistry, Division of Analytical Pharmaceutical Chemistry, Uppsala University (Sweden); Haglöf, Jakob; Engskog, Mikael K.R. [Department of Medicinal Chemistry, Division of Analytical Pharmaceutical Chemistry, Uppsala University (Sweden); Nestor, Marika [Department of Immunology, Genetics and Pathology, Uppsala University (Sweden); Arvidsson, Torbjörn [Department of Medicinal Chemistry, Division of Analytical Pharmaceutical Chemistry, Uppsala University (Sweden); Medical Product Agency, Uppsala (Sweden); Pettersson, Curt [Department of Medicinal Chemistry, Division of Analytical Pharmaceutical Chemistry, Uppsala University (Sweden)

    2017-03-01

    Evaluation of analytical procedures, especially in regards to measuring chromatographic and signal selectivity, is highly challenging in untargeted metabolomics. The aim of this study was to suggest a new straightforward approach for a systematic examination of chromatographic and signal selectivity in LC-MS-based metabolomics. By calculating the ratio between each feature and its co-eluting features (the co-features), a measurement of the chromatographic selectivity (i.e. extent of co-elution) as well as the signal selectivity (e.g. amount of adduct formation) of each feature could be acquired, the co-feature ratio. This approach was used to examine possible differences in chromatographic and signal selectivity present in samples exposed to three different sample preparation procedures. The capability of the co-feature ratio was evaluated both in a classical targeted setting using isotope labelled standards as well as without standards in an untargeted setting. For the targeted analysis, several metabolites showed a skewed quantitative signal due to poor chromatographic selectivity and/or poor signal selectivity. Moreover, evaluation of the untargeted approach through multivariate analysis of the co-feature ratios demonstrated the possibility to screen for metabolites displaying poor chromatographic and/or signal selectivity characteristics. We conclude that the co-feature ratio can be a useful tool in the development and evaluation of analytical procedures in LC-MS-based metabolomics investigations. Increased selectivity through proper choice of analytical procedures may decrease the false positive and false negative discovery rate and thereby increase the validity of any metabolomic investigation. - Highlights: • The co-feature ratio (CFR) is introduced. • CFR measures chromatographic and signal selectivity of a feature. • CFR can be used for evaluating experimental procedures in metabolomics. • CFR can aid in locating features with poor selectivity.

  8. Development and Validation of a High-Throughput Mass Spectrometry Based Urine Metabolomic Test for the Detection of Colonic Adenomatous Polyps.

    Science.gov (United States)

    Deng, Lu; Chang, David; Foshaug, Rae R; Eisner, Roman; Tso, Victor K; Wishart, David S; Fedorak, Richard N

    2017-06-22

    Background: Colorectal cancer is one of the leading causes of cancer deaths worldwide. The detection and removal of the precursors to colorectal cancer, adenomatous polyps, is the key for screening. The aim of this study was to develop a clinically scalable (high throughput, low cost, and high sensitivity) mass spectrometry (MS)-based urine metabolomic test for the detection of adenomatous polyps. Methods : Prospective urine and stool samples were collected from 685 participants enrolled in a colorectal cancer screening program to undergo colonoscopy examination. Statistical analysis was performed on 69 urine metabolites measured by one-dimensional nuclear magnetic resonance spectroscopy to identify key metabolites. A targeted MS assay was then developed to quantify the key metabolites in urine. A MS-based urine metabolomic diagnostic test for adenomatous polyps was established using 67% samples (un-blinded training set) and validated using the remaining 33% samples (blinded testing set). Results : The MS-based urine metabolomic test identifies patients with colonic adenomatous polyps with an AUC of 0.692, outperforming the NMR based predictor with an AUC of 0.670. Conclusion : Here we describe a clinically scalable MS-based urine metabolomic test that identifies patients with adenomatous polyps at a higher level of sensitivity (86%) over current fecal-based tests (<18%).

  9. Development and Validation of a High-Throughput Mass Spectrometry Based Urine Metabolomic Test for the Detection of Colonic Adenomatous Polyps

    Directory of Open Access Journals (Sweden)

    Lu Deng

    2017-06-01

    Full Text Available Background: Colorectal cancer is one of the leading causes of cancer deaths worldwide. The detection and removal of the precursors to colorectal cancer, adenomatous polyps, is the key for screening. The aim of this study was to develop a clinically scalable (high throughput, low cost, and high sensitivity mass spectrometry (MS-based urine metabolomic test for the detection of adenomatous polyps. Methods: Prospective urine and stool samples were collected from 685 participants enrolled in a colorectal cancer screening program to undergo colonoscopy examination. Statistical analysis was performed on 69 urine metabolites measured by one-dimensional nuclear magnetic resonance spectroscopy to identify key metabolites. A targeted MS assay was then developed to quantify the key metabolites in urine. A MS-based urine metabolomic diagnostic test for adenomatous polyps was established using 67% samples (un-blinded training set and validated using the remaining 33% samples (blinded testing set. Results: The MS-based urine metabolomic test identifies patients with colonic adenomatous polyps with an AUC of 0.692, outperforming the NMR based predictor with an AUC of 0.670. Conclusion: Here we describe a clinically scalable MS-based urine metabolomic test that identifies patients with adenomatous polyps at a higher level of sensitivity (86% over current fecal-based tests (<18%.

  10. Enantioselective Effects of Metalaxyl Enantiomers on Breast Cancer Cells Metabolic Profiling Using HPLC-QTOF-Based Metabolomics

    Directory of Open Access Journals (Sweden)

    Ping Zhang

    2017-01-01

    Full Text Available In this study, an integrative high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (HPLC-QTOF based metabolomics approach was performed to evaluate the enantioselective metabolic perturbations in MCF-7 cells after treatment with R-metalaxyl and S-metalaxyl, respectively. Untargeted metabolomics profile, multivariate pattern recognition, metabolites identification, and pathway analysis were determined after metalaxyl enantiomer exposure. Principal component analysis (PCA and partitial least-squares discriminant analysis (PLS-DA directly reflected the enantioselective metabolic perturbations induced by metalaxyl enantiomers. On the basis of multivariate statistical results, a total of 49 metabolites including carbohydrates, amino acids, nucleotides, fatty acids, organic acids, phospholipids, indoles, derivatives, etc. were found to be the most significantly changed metabolites and metabolic fluctuations caused by the same concentration of R-metalaxyl and S-metalaxyl were enantioselective. Pathway analysis indicated that R-metalaxyl and S-metalaxyl mainly affected the 7 and 10 pathways in MCF-7 cells, respectively, implying the perturbed pathways induced by metalaxyl enantiomers were also enantioselective. Furthermore, the significantly perturbed metabolic pathways were highly related to energy metabolism, amino acid metabolism, lipid metabolism, and antioxidant defense. Such results provide more specific insights into the enantioselective metabolic effects of chiral pesticides in breast cancer progression, reveal the underlying mechanisms, and provide available data for the health risk assessments of chiral environmental pollutants at the molecular level.

  11. Enantioselective Effects of Metalaxyl Enantiomers on Breast Cancer Cells Metabolic Profiling Using HPLC-QTOF-Based Metabolomics.

    Science.gov (United States)

    Zhang, Ping; Zhu, Wentao; Wang, Dezhen; Yan, Jin; Wang, Yao; He, Lin

    2017-01-12

    In this study, an integrative high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry (HPLC-QTOF) based metabolomics approach was performed to evaluate the enantioselective metabolic perturbations in MCF-7 cells after treatment with R -metalaxyl and S -metalaxyl, respectively. Untargeted metabolomics profile, multivariate pattern recognition, metabolites identification, and pathway analysis were determined after metalaxyl enantiomer exposure. Principal component analysis (PCA) and partitial least-squares discriminant analysis (PLS-DA) directly reflected the enantioselective metabolic perturbations induced by metalaxyl enantiomers. On the basis of multivariate statistical results, a total of 49 metabolites including carbohydrates, amino acids, nucleotides, fatty acids, organic acids, phospholipids, indoles, derivatives, etc. were found to be the most significantly changed metabolites and metabolic fluctuations caused by the same concentration of R -metalaxyl and S -metalaxyl were enantioselective. Pathway analysis indicated that R -metalaxyl and S -metalaxyl mainly affected the 7 and 10 pathways in MCF-7 cells, respectively, implying the perturbed pathways induced by metalaxyl enantiomers were also enantioselective. Furthermore, the significantly perturbed metabolic pathways were highly related to energy metabolism, amino acid metabolism, lipid metabolism, and antioxidant defense. Such results provide more specific insights into the enantioselective metabolic effects of chiral pesticides in breast cancer progression, reveal the underlying mechanisms, and provide available data for the health risk assessments of chiral environmental pollutants at the molecular level.

  12. UPLC-Q-TOF/MS based metabolomic profiling of serum and urine of hyperlipidemic rats induced by high fat diet

    Directory of Open Access Journals (Sweden)

    Qiong Wu

    2014-12-01

    Full Text Available Hyperlipidemia is considered to be a high lipid level in blood, can induce metabolic disorders and dysfunctions of the body, and results in some severe complications. Therefore, hunting for some metabolite markers and clarifying the metabolic pathways in vivo will be an important strategy in the treatment and prevention of hyperlipidemia. In this study, a rat model of hyperlipidemia was constructed according to histopathological data and biochemical parameters, and the metabolites of serum and urine were analyzed by UPLC-Q-TOF/MS. Combining pattern recognition and statistical analysis, 19 candidate biomarkers were screened and identified. These changed metabolites indicated that during the development and progression of hyperlipidemia, energy metabolism, lipid metabolism, amino acid metabolism and nucleotide metabolism were mainly disturbed, which are reported to be closely related to diabetes, cardiovascular diseases, etc. This study demonstrated that a UPLC-Q-TOF/MS based metabolomic approach is useful to profile the alternation of endogenous metabolites of hyperlipidemia. Keywords: UPLC-Q-TOF/MS, Hyperlipidemia, Metabolomic, Pattern recognition

  13. Metabolomic-Based Study of the Leafy Gall, the Ecological Niche of the Phytopathogen Rhodococcus fascians, as a Potential Source of Bioactive Compounds

    Directory of Open Access Journals (Sweden)

    Pierre Duez

    2013-06-01

    Full Text Available Leafy gall is a plant hyperplasia induced upon Rhodococcus fascians infection. Previously, by genomic and transcriptomic analysis, it has been reported that, at the early stage of symptom development, both primary and secondary metabolisms are modified. The present study is based on the hypothesis that fully developed leafy gall, could represent a potential source of new bioactive compounds. Therefore, non-targeted metabolomic analysis of aqueous and chloroform extracts of leafy gall and non-infected tobacco was carried out by 1H-NMR coupled to principal component analysis (PCA and orthogonal projections to latent structures-discriminant analysis (OPLS-DA. Polar metabolite profiling reflects modifications mainly in the primary metabolites and in some polyphenolics. In contrast, main modifications occurring in non-polar metabolites concern secondary metabolites, and gas chromatography and mass spectrometry (GC-MS evidenced alterations in diterpenoids family. Analysis of crude extracts of leafy galls and non-infected tobacco leaves exhibited a distinct antiproliferative activity against all four tested human cancer cell lines. A bio-guided fractionation of chloroformic crude extract yield to semi-purified fractions, which inhibited proliferation of glioblastoma U373 cells with IC50 between 14.0 and 2.4 µg/mL. Discussion is focused on the consequence of these metabolic changes, with respect to plant defense mechanisms following infection. Considering the promising role of diterpenoid family as bioactive compounds, leafy gall may rather be a propitious source for drug discovery.

  14. Metabolomics Characterization of Two Apocynaceae Plants, Catharanthus roseus and Vinca minor, Using GC-MS and LC-MS Methods in Combination.

    Science.gov (United States)

    Chen, Qi; Lu, Xueyan; Guo, Xiaorui; Guo, Qingxi; Li, Dewen

    2017-06-17

    Catharanthus roseus ( C. roseus ) and Vinca minor ( V. minor ) are two common important medical plants belonging to the family Apocynaceae. In this study, we used non-targeted GC-MS and targeted LC-MS metabolomics to dissect the metabolic profile of two plants with comparable phenotypic and metabolic differences. A total of 58 significantly different metabolites were present in different quantities according to PCA and PLS-DA score plots of the GC-MS analysis. The 58 identified compounds comprised 16 sugars, eight amino acids, nine alcohols and 18 organic acids. We subjected these metabolites into KEGG pathway enrichment analysis and highlighted 27 metabolic pathways, concentrated on the TCA cycle, glycometabolism, oligosaccharides, and polyol and lipid transporter (RFOS). Among the primary metabolites, trehalose, raffinose, digalacturonic acid and gallic acid were revealed to be the most significant marker compounds between the two plants, presumably contributing to species-specific phenotypic and metabolic discrepancy. The profiling of nine typical alkaloids in both plants using LC-MS method highlighted higher levels of crucial terpenoid indole alkaloid (TIA) intermediates of loganin, serpentine, and tabersonine in V. minor than in C. roseus . The possible underlying process of the metabolic flux from primary metabolism pathways to TIA synthesis was discussed and proposed. Generally speaking, this work provides a full-scale comparison of primary and secondary metabolites between two medical plants and a metabolic explanation of their TIA accumulation and phenotype differences.

  15. GC-MS Metabolomics to Evaluate the Composition of Plant Cuticular Waxes for Four Triticum aestivum Cultivars

    Directory of Open Access Journals (Sweden)

    Florent D. Lavergne

    2018-01-01

    Full Text Available Wheat (Triticum aestivum L. is an important food crop, and biotic and abiotic stresses significantly impact grain yield. Wheat leaf and stem surface waxes are associated with traits of biological importance, including stress resistance. Past studies have characterized the composition of wheat cuticular waxes, however protocols can be relatively low-throughput and narrow in the range of metabolites detected. Here, gas chromatography-mass spectrometry (GC-MS metabolomics methods were utilized to provide a comprehensive characterization of the chemical composition of cuticular waxes in wheat leaves and stems. Further, waxes from four wheat cultivars were assayed to evaluate the potential for GC-MS metabolomics to describe wax composition attributed to differences in wheat genotype. A total of 263 putative compounds were detected and included 58 wax compounds that can be classified (e.g., alkanes and fatty acids. Many of the detected wax metabolites have known associations to important biological functions. Principal component analysis and ANOVA were used to evaluate metabolite distribution, which was attributed to both tissue type (leaf, stem and cultivar differences. Leaves contained more primary alcohols than stems such as 6-methylheptacosan-1-ol and octacosan-1-ol. The metabolite data were validated using scanning electron microscopy of epicuticular wax crystals which detected wax tubules and platelets. Conan was the only cultivar to display alcohol-associated platelet-shaped crystals on its abaxial leaf surface. Taken together, application of GC-MS metabolomics enabled the characterization of cuticular wax content in wheat tissues and provided relative quantitative comparisons among sample types, thus contributing to the understanding of wax composition associated with important phenotypic traits in a major crop.

  16. Interstitial Cystitis-Associated Urinary Metabolites Identified by Mass-Spectrometry Based Metabolomics Analysis

    Science.gov (United States)

    Kind, Tobias; Cho, Eunho; Park, Taeeun D.; Deng, Nan; Liu, Zhenqiu; Lee, Tack; Fiehn, Oliver; Kim, Jayoung

    2016-01-01

    This study on interstitial cystitis (IC) aims to identify a unique urine metabolomic profile associated with IC, which can be defined as an unpleasant sensation including pain and discomfort related to the urinary bladder, without infection or other identifiable causes. Although the burden of IC on the American public is immense in both human and financial terms, there is no clear diagnostic test for IC, but rather it is a disease of exclusion. Very little is known about the clinically useful urinary biomarkers of IC, which are desperately needed. Untargeted comprehensive metabolomic profiling was performed using gas-chromatography/mass-spectrometry to compare urine specimens of IC patients or health donors. The study profiled 200 known and 290 unknown metabolites. The majority of the thirty significantly changed metabolites before false discovery rate correction were unknown compounds. Partial least square discriminant analysis clearly separated IC patients from controls. The high number of unknown compounds hinders useful biological interpretation of such predictive models. Given that urine analyses have great potential to be adapted in clinical practice, research has to be focused on the identification of unknown compounds to uncover important clues about underlying disease mechanisms. PMID:27976711

  17. An untargeted metabolomic assessment of cocoa beans during fermentation

    OpenAIRE

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

    2016-01-01

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

  18. Standardizing the experimental conditions for using urine in NMR-based metabolomic studies with a particular focus on diagnostic studies: a review

    KAUST Repository

    Emwas, Abdul-Hamid M.

    2014-11-21

    The metabolic composition of human biofluids can provide important diagnostic and prognostic information. Among the biofluids most commonly analyzed in metabolomic studies, urine appears to be particularly useful. It is abundant, readily available, easily stored and can be collected by simple, noninvasive techniques. Moreover, given its chemical complexity, urine is particularly rich in potential disease biomarkers. This makes it an ideal biofluid for detecting or monitoring disease processes. Among the metabolomic tools available for urine analysis, NMR spectroscopy has proven to be particularly well-suited, because the technique is highly reproducible and requires minimal sample handling. As it permits the identification and quantification of a wide range of compounds, independent of their chemical properties, NMR spectroscopy has been frequently used to detect or discover disease fingerprints and biomarkers in urine. Although protocols for NMR data acquisition and processing have been standardized, no consensus on protocols for urine sample selection, collection, storage and preparation in NMR-based metabolomic studies have been developed. This lack of consensus may be leading to spurious biomarkers being reported and may account for a general lack of reproducibility between laboratories. Here, we review a large number of published studies on NMR-based urine metabolic profiling with the aim of identifying key variables that may affect the results of metabolomics studies. From this survey, we identify a number of issues that require either standardization or careful accounting in experimental design and provide some recommendations for urine collection, sample preparation and data acquisition.

  19. {sup 1}H NMR-based metabolomics of time-dependent responses of Eisenia fetida to sub-lethal phenanthrene exposure

    Energy Technology Data Exchange (ETDEWEB)

    Lankadurai, Brian P.; Wolfe, David M.; Simpson, Andre J. [Department of Chemistry, University of Toronto, 1265 Military Trail, Toronto, Ontario M1C 1A4 Canada (Canada); Simpson, Myrna J., E-mail: myrna.simpson@utoronto.ca [Department of Chemistry, University of Toronto, 1265 Military Trail, Toronto, Ontario M1C 1A4 Canada (Canada)

    2011-10-15

    {sup 1}H NMR-based metabolomics was used to examine the response of the earthworm Eisenia fetida after exposure to sub-lethal concentrations of phenanthrene over time. Earthworms were exposed to 0.025 mg/cm{sup 2} of phenanthrene (1/64th of the LC{sub 50}) via contact tests over four days. Earthworm tissues were extracted using a mixture of chloroform, methanol and water, resulting in polar and non-polar fractions that were analyzed by {sup 1}H NMR after one, two, three and four days. NMR-based metabolomic analyses revealed heightened E. fetida responses with longer phenanthrene exposure times. Amino acids alanine and glutamate, the sugar maltose, the lipids cholesterol and phosphatidylcholine emerged as potential indicators of phenanthrene exposure. The conversion of succinate to fumarate in the Krebs cycle was also interrupted by phenanthrene. Therefore, this study shows that NMR-based metabolomics is a powerful tool for elucidating time-dependent relationships in addition to the mode of toxicity of phenanthrene in earthworm exposure studies. - Highlights: > NMR-based earthworm metabolomic analysis of the mode of action of phenanthrene is presented. > The earthworm species E. fetida were exposed to sub-lethal phenanthrene concentrations. > Both polar and non-polar metabolites of E. fetida tissue extracts were analyzed by {sup 1}H NMR. > Longer phenanthrene exposure times resulted in heightened earthworm responses. > An interruption of the Krebs cycle was also observed due to phenanthrene exposure. - {sup 1}H NMR metabolomics is used to determine the relationship between phenanthrene exposure and the metabolic response of the earthworm E. fetida over time and also to elucidate the phenanthrene mode of toxicity.

  20. Quality evaluation of extracted ion chromatograms and chromatographic peaks in liquid chromatography/mass spectrometry-based metabolomics data.

    Science.gov (United States)

    Zhang, Wenchao; Zhao, Patrick X

    2014-01-01

    Extracted ion chromatogram (EIC) extraction and chromatographic peak detection are two important processing procedures in liquid chromatography/mass spectrometry (LC/MS)-based metabolomics data analysis. Most commonly, the LC/MS technique employs electrospray ionization as the ionization method. The EICs from LC/MS data are often noisy and contain high background signals. Furthermore, the chromatographic peak quality varies with respect to its location in the chromatogram and most peaks have zigzag shapes. Therefore, there is a critical need to develop effective metrics for quality evaluation of EICs and chromatographic peaks in LC/MS based metabolomics data analysis. We investigated a comprehensive set of potential quality evaluation metrics for extracted EICs and detected chromatographic peaks. Specifically, for EIC quality evaluation, we analyzed the mass chromatographic quality index (MCQ index) and propose a novel quality evaluation metric, the EIC-related global zigzag index, which is based on an EIC's first order derivatives. For chromatographic peak quality evaluation, we analyzed and compared six metrics: sharpness, Gaussian similarity, signal-to-noise ratio, peak significance level, triangle peak area similarity ratio and the local peak-related local zigzag index. Although the MCQ index is suited for selecting and aligning analyte components, it cannot fairly evaluate EICs with high background signals or those containing only a single peak. Our proposed EIC related global zigzag index is robust enough to evaluate EIC qualities in both scenarios. Of the six peak quality evaluation metrics, the sharpness, peak significance level, and zigzag index outperform the others due to the zigzag nature of LC/MS chromatographic peaks. Furthermore, using several peak quality metrics in combination is more efficient than individual metrics in peak quality evaluation.

  1. Elucidation of cellular metabolism via metabolomics and stable-isotope assisted metabolomics.

    Science.gov (United States)

    Hiller, Karsten; Metallo, Christian; Stephanopoulos, Gregory

    2011-07-01

    Metabolomics and metabolic flux analysis (MFA) are powerful tools in the arsenal of methodologies of systems biology. Currently, metabolomics techniques are applied routinely for biomarker determination. However, standard metabolomics techniques only provide static information about absolute or relative metabolite amounts. The application of stable-isotope tracers has opened up a new dimension to metabolomics by providing dynamic information of intracellular fluxes and, by extension, enzyme activities. In the first part of the manuscript we review experimental and computational technologies applicable for metabolomics analyses. In the second part we present current technologies based on the use of stable isotopes and their applications to the analysis of cellular metabolism. Beginning with the determination of mass isotopomer distributions (MIDs), we review technologies for metabolic flux analysis (MFA) and conclude with the presentation of a new methodology for the non-targeted analysis of stable-isotope labeled metabolomics data.

  2. IDEOM: an Excel interface for analysis of LC-MS-based metabolomics data.

    Science.gov (United States)

    Creek, Darren J; Jankevics, Andris; Burgess, Karl E V; Breitling, Rainer; Barrett, Michael P

    2012-04-01

    The application of emerging metabolomics technologies to the comprehensive investigation of cellular biochemistry has been limited by bottlenecks in data processing, particularly noise filtering and metabolite identification. IDEOM provides a user-friendly data processing application that automates filtering and identification of metabolite peaks, paying particular attention to common sources of noise and false identifications generated by liquid chromatography-mass spectrometry (LC-MS) platforms. Building on advanced processing tools such as mzMatch and XCMS, it allows users to run a comprehensive pipeline for data analysis and visualization from a graphical user interface within Microsoft Excel, a familiar program for most biological scientists. IDEOM is provided free of charge at http://mzmatch.sourceforge.net/ideom.html, as a macro-enabled spreadsheet (.xlsb). Implementation requires Microsoft Excel (2007 or later). R is also required for full functionality. michael.barrett@glasgow.ac.uk Supplementary data are available at Bioinformatics online.

  3. Variable importance analysis based on rank aggregation with applications in metabolomics for biomarker discovery.

    Science.gov (United States)

    Yun, Yong-Huan; Deng, Bai-Chuan; Cao, Dong-Sheng; Wang, Wei-Ting; Liang, Yi-Zeng

    2016-03-10

    Biomarker discovery is one important goal in metabolomics, which is typically modeled as selecting the most discriminating metabolites for classification and often referred to as variable importance analysis or variable selection. Until now, a number of variable importance analysis methods to discover biomarkers in the metabolomics studies have been proposed. However, different methods are mostly likely to generate different variable ranking results due to their different principles. Each method generates a variable ranking list just as an expert presents an opinion. The problem of inconsistency between different variable ranking methods is often ignored. To address this problem, a simple and ideal solution is that every ranking should be taken into account. In this study, a strategy, called rank aggregation, was employed. It is an indispensable tool for merging individual ranking lists into a single "super"-list reflective of the overall preference or importance within the population. This "super"-list is regarded as the final ranking for biomarker discovery. Finally, it was used for biomarkers discovery and selecting the best variable subset with the highest predictive classification accuracy. Nine methods were used, including three univariate filtering and six multivariate methods. When applied to two metabolic datasets (Childhood overweight dataset and Tubulointerstitial lesions dataset), the results show that the performance of rank aggregation has improved greatly with higher prediction accuracy compared with using all variables. Moreover, it is also better than penalized method, least absolute shrinkage and selectionator operator (LASSO), with higher prediction accuracy or less number of selected variables which are more interpretable. Copyright © 2016 Elsevier B.V. All rights reserved.

  4. A metabolomic study in oats (Avena sativa) highlights a drought tolerance mechanism based upon salicylate signalling pathways and the modulation of carbon, antioxidant and photo-oxidative metabolism.

    Science.gov (United States)

    Sánchez-Martín, Javier; Heald, Jim; Kingston-Smith, Alison; Winters, Ana; Rubiales, Diego; Sanz, Mariluz; Mur, Luis A J; Prats, Elena

    2015-07-01

    Although a wealth of information is available on the induction of one or several drought-related responses in different species, little is known of how their timing, modulation and crucially integration influence drought tolerance. Based upon metabolomic changes in oat (Avena sativa L.), we have defined key processes involved in drought tolerance. During a time course of increasing water deficit, metabolites from leaf samples were profiled using direct infusion-electrospray mass spectroscopy (DI-ESI-MS) and high-performance liquid chromatography (HPLC) ESI-MS/MS and analysed using principal component analysis (PCA) and discriminant function analysis (DFA). The involvement of metabolite pathways was confirmed through targeted assays of key metabolites and physiological experiments. We demonstrate an early accumulation of salicylic acid (SA) influencing stomatal opening, photorespiration and antioxidant defences before any change in the relative water content. These changes are likely to maintain plant water status, with any photoinhibitory effect being counteracted by an efficient antioxidant capacity, thereby representing an integrated mechanism of drought tolerance in oats. We also discuss these changes in relation to those engaged at later points, consequence of the different water status in susceptible and resistant genotypes. © 2014 John Wiley & Sons Ltd.

  5. A new metabolomics-based strategy for identification of endogenous markers of urine adulteration attempts exemplified for potassium nitrite.

    Science.gov (United States)

    Steuer, Andrea E; Arnold, Kim; Schneider, Tom D; Poetzsch, Michael; Kraemer, Thomas

    2017-10-01

    Urine adulteration to circumvent positive drug testing represents a problem for toxicological laboratories. While creatinine is a suitable marker for dilution, detection of chemicals is often performed by dipstick tests associated with high rates of false positives. Several methods would be necessary to check for all possible adulterants. Untargeted mass spectrometry (MS) methods used in metabolomics should theoretically allow detecting concentration changes of any endogenous urinary metabolite or presence of new biomarkers produced by chemical adulteration. As a proof of concept study, urine samples from 10 volunteers were treated with KNO 2 and analyzed by high-resolution MS. For statistical data evaluation, XCMS plus and MetaboAnalyst were used. Compound identification was performed by database searches using an in-house database, Chemspider, METLIN, HMDB, and NIST. Principle component analysis revealed clear separation between treated and untreated urine samples. In detail, 307 features showed significant concentration changes with fold changes greater than 2 (79 decreased; 228 increased). Mainly amino acids (e.g., histidine, methylhistidine, di- and trimethyllysine) and purines (uric acid) were detected in lower amounts. 5-HO-isourate was found to be formed as a new compound from uric acid and, e.g., imidazole lactate concentrations increased due to the breakdown of histidine. This metabolomics-based strategy allowed for a broad identification range of markers of urinary adulteration. More studies will be needed to investigate routine applicability of identified potential markers exploring urinary conditions of their formation and stability. Selected markers might then be integrated into routine MS screening procedures allowing for detection of adulteration within routine MS analysis. Graphical Abstract ᅟ.

  6. 1H NMR-based metabolomics investigation of copper-laden rat: a model of Wilson's disease.

    Directory of Open Access Journals (Sweden)

    Jingjing Xu

    Full Text Available Wilson's disease (WD, also known as hepatoleticular degeneration (HLD, is a rare autosomal recessive genetic disorder of copper metabolism, which causes copper to accumulate in body tissues. In this study, rats fed with copper-laden diet are used to render the clinical manifestations of WD, and their copper toxicity-induced organ lesions are studied. To investigate metabolic behaviors of 'decoppering' process, penicillamine (PA was used for treating copper-laden rats as this chelating agent could eliminate excess copper through the urine. To date, there has been limited metabolomics study on WD, while metabolic impacts of copper accumulation and PA administration have yet to be established.A combination of 1HNMR spectroscopy and multivariate statistical analysis was applied to examine the metabolic profiles of the urine and blood serum samples collected from the copper-laden rat model of WD with PA treatment.Copper accumulation in the copper-laden rats is associated with increased lactate, creatinine, valine and leucine, as well as decreased levels of glucose and taurine in the blood serum. There were also significant changes in p-hydroxyphenylacetate (p-HPA, creatinine, alpha-ketoglutarate (α-KG, dimethylamine, N-acetylglutamate (NAG, N-acetylglycoprotein (NAC in the urine of these rats. Notably, the changes in p-HPA, glucose, lactate, taurine, valine, leucine, and NAG were found reversed following PA treatment. Nevertheless, there were no changes for dimethylamine, α-KG, and NAC as a result of the treatment. Compared with the controls, the concentrations of hippurate, formate, alanine, and lactate were changed when PA was applied and this is probably due to its side effect. A tool named SMPDB (Small Molecule Pathway Database is introduced to identify the metabolic pathway influenced by the copper-laden diet.The study has shown the potential application of NMR-based metabolomic analysis in providing further insights into the molecular

  7. The future of metabolomics in ELIXIR.

    Science.gov (United States)

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

    2017-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Abirami eRamalingam

    2015-12-01

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

  9. Discrimination of three Siegesbeckiae Herba species using UPLC-QTOF/MS-based metabolomics approach.

    Science.gov (United States)

    Tao, Hong-Xun; Xiong, Wei; Zhao, Guan-Ding; Peng, Yu; Zhong, Zhang-Feng; Xu, Liang; Duan, Ran; Tsim, Karl W K; Yu, Hua; Wang, Yi-Tao

    2018-01-03

    The plant origin is one of the most important factors for the quality control of traditional Chinese medicines (TCMs) and highly affected on their safety and effectiveness in clinical applications. Multi-origin has been widely observed for many TCMs. Siegesbeckiae Herba (SH) is a traditional anti-rheumatic TCM which is originated from the plants of Siegesbeckia pubescens Makino (SP), S. orientalis L. (SO), and S. glabrescens Makino (SG). In the present study, an UPLC-QTOF/MS method were validated and successfully applied for the determination of the chemical profiles in the three SH species. The data were statistical analyzed with the OPLS-DA analysis and One-Way ANOVA F-test. Obvious differences in chemistry were observed in different SH species and 40 components were identified. Finally, 6 components were selected as potential chemical markers for the discrimination of SP, SO and SG based on the characteristic distribution in individual SH species. Copyright © 2017. Published by Elsevier Ltd.

  10. 1H-NMR and MS Based Metabolomics Study of the Intervention Effect of Curcumin on Hyperlipidemia Mice Induced by High-Fat Diet

    OpenAIRE

    Li, Ze-Yun; Ding, Li-Li; Li, Jin-Mei; Xu, Bao-Li; Yang, Li; Bi, Kai-Shun; Wang, Zheng-Tao

    2015-01-01

    Curcumin, a principle bioactive component of Curcuma longa L, is well known for its anti-hyperlipidemia effect. However, no holistic metabolic information of curcumin on hyperlipidemia models has been revealed, which may provide us an insight into the underlying mechanism. In the present work, NMR and MS based metabolomics was conducted to investigate the intervention effect of curcumin on hyperlipidemia mice induced by high-fat diet (HFD) feeding for 12 weeks. The HFD induced animals were or...

  11. Development and Validation of a High-Throughput Mass Spectrometry Based Urine Metabolomic Test for the Detection of Colonic Adenomatous Polyps

    OpenAIRE

    Deng, Lu; Chang, David; Foshaug, Rae R.; Eisner, Roman; Tso, Victor K.; Wishart, David S.; Fedorak, Richard N.

    2017-01-01

    Background: Colorectal cancer is one of the leading causes of cancer deaths worldwide. The detection and removal of the precursors to colorectal cancer, adenomatous polyps, is the key for screening. The aim of this study was to develop a clinically scalable (high throughput, low cost, and high sensitivity) mass spectrometry (MS)-based urine metabolomic test for the detection of adenomatous polyps. Methods: Prospective urine and stool samples were collected from 685 participants enrolled in a ...

  12. UPLC/Q-TOF-MS-based metabolomics study of the anti-osteoporosis effects of Achyranthes bidentata polysaccharides in ovariectomized rats.

    Science.gov (United States)

    Zhang, Mengliu; Wang, Yang; Zhang, Qian; Wang, Changsheng; Zhang, Dawei; Wan, Jian-Bo; Yan, Chunyan

    2018-06-01

    Osteoporosis is a frequent disease among the elderly especially in postmenopausal women. Achyranthes bidentata is a traditional Chinese medicine used to strengthen bones. Here, A. bidentata polysaccharides (ABPs) were confirmed to have anti-osteoporosis effects. This study discovered biomarkers by comparing normal and osteoporosis rats and evaluated the effects of ABPs on osteoporosis based on the UPLC/Q-TOF-MS-based metabolomics analysis. We could then predict the underlying mechanisms from the perspective of metabolomics. Osteoporotic rats were treated with ABPs, and serum was then sampled for metabolic analysis. Glutarylcarnitine, lysoPC (18:1) and 9-cis-retinoic acid were identified as biomarkers. The ABPs could significantly increase these biomarkers, and this indicated that ABPs curing osteoporosis regulated lipid metabolism. The UPLC/Q-TOF-MS-based metabolomics analysis offered a potential strategy to evaluate the anti-osteoporosis effects of ABPs and to explain the relative mechanisms. Furthermore, the ABPs have good potential for treating osteoporosis. Copyright © 2018 Elsevier B.V. All rights reserved.

  13. 1H NMR-Based Metabolomic Analysis of Sub-Lethal Perfluorooctane Sulfonate Exposure to the Earthworm, Eisenia fetida, in Soil

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    Myrna J. Simpson

    2013-08-01

    Full Text Available 1H NMR-based metabolomics was used to measure the response of Eisenia fetida earthworms after exposure to sub-lethal concentrations of perfluorooctane sulfonate (PFOS in soil. Earthworms were exposed to a range of PFOS concentrations (five, 10, 25, 50, 100 or 150 mg/kg for two, seven and fourteen days. Earthworm tissues were extracted and analyzed by 1H NMR. Multivariate statistical analysis of the metabolic response of E. fetida to PFOS exposure identified time-dependent responses that were comprised of two separate modes of action: a non-polar narcosis type mechanism after two days of exposure and increased fatty acid oxidation after seven and fourteen days of exposure. Univariate statistical analysis revealed that 2-hexyl-5-ethyl-3-furansulfonate (HEFS, betaine, leucine, arginine, glutamate, maltose and ATP are potential indicators of PFOS exposure, as the concentrations of these metabolites fluctuated significantly. Overall, NMR-based metabolomic analysis suggests elevated fatty acid oxidation, disruption in energy metabolism and biological membrane structure and a possible interruption of ATP synthesis. These conclusions obtained from analysis of the metabolic profile in response to sub-lethal PFOS exposure indicates that NMR-based metabolomics is an excellent discovery tool when the mode of action (MOA of contaminants is not clearly defined.

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

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    Mohana Krishna Reddy Mudiam

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

  15. Gas chromatography time-of-flight mass spectrometry (GC-TOF-MS-based metabolomics for comparison of caffeinated and decaffeinated coffee and its implications for Alzheimer's disease.

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    Kai Lun Chang

    Full Text Available Findings from epidemiology, preclinical and clinical studies indicate that consumption of coffee could have beneficial effects against dementia and Alzheimer's disease (AD. The benefits appear to come from caffeinated coffee, but not decaffeinated coffee or pure caffeine itself. Therefore, the objective of this study was to use metabolomics approach to delineate the discriminant metabolites between caffeinated and decaffeinated coffee, which could have contributed to the observed therapeutic benefits. Gas chromatography time-of-flight mass spectrometry (GC-TOF-MS-based metabolomics approach was employed to characterize the metabolic differences between caffeinated and decaffeinated coffee. Orthogonal partial least squares discriminant analysis (OPLS-DA showed distinct separation between the two types of coffee (cumulative Q(2 = 0.998. A total of 69 discriminant metabolites were identified based on the OPLS-DA model, with 37 and 32 metabolites detected to be higher in caffeinated and decaffeinated coffee, respectively. These metabolites include several benzoate and cinnamate-derived phenolic compounds, organic acids, sugar, fatty acids, and amino acids. Our study successfully established GC-TOF-MS based metabolomics approach as a highly robust tool in discriminant analysis between caffeinated and decaffeinated coffee samples. Discriminant metabolites identified in this study are biologically relevant and provide valuable insights into therapeutic research of coffee against AD. Our data also hint at possible involvement of gut microbial metabolism to enhance therapeutic potential of coffee components, which represents an interesting area for future research.

  16. An untargeted global metabolomic analysis reveals the biochemical changes underlying basal resistance and priming in Solanum lycopersicum, and identifies 1-methyltryptophan as a metabolite involved in plant responses to Botrytis cinerea and Pseudomonas syringae.

    Science.gov (United States)

    Camañes, Gemma; Scalschi, Loredana; Vicedo, Begonya; González-Bosch, Carmen; García-Agustín, Pilar

    2015-10-01

    In this study, we have used untargeted global metabolomic analysis to determine and compare the chemical nature of the metabolites altered during the infection of tomato plants (cv. Ailsa Craig) with Botrytis cinerea (Bot) or Pseudomonas syringae pv. tomato DC3000 (Pst), pathogens that have different invasion mechanisms and lifestyles. We also obtained the metabolome of tomato plants primed using the natural resistance inducer hexanoic acid and then infected with these pathogens. By contrasting the metabolomic profiles of infected, primed, and primed + infected plants, we determined not only the processes or components related directly to plant defense responses, but also inferred the metabolic mechanisms by which pathogen resistance is primed. The data show that basal resistance and hexanoic acid-induced resistance to Bot and Pst are associated with a marked metabolic reprogramming. This includes significant changes in amino acids, sugars and free fatty acids, and in primary and secondary metabolism. Comparison of the metabolic profiles of the infections indicated clear differences, reflecting the fact that the plant's chemical responses are highly adapted to specific attackers. The data also indicate involvement of signaling molecules, including pipecolic and azelaic acids, in response to Pst and, interestingly, to Bot. The compound 1-methyltryptophan was shown to be associated with the tomato-Pst and tomato-Bot interactions as well as with hexanoic acid-induced resistance. Root application of this Trp-derived metabolite also demonstrated its ability to protect tomato plants against both pathogens. © 2015 The Authors The Plant Journal © 2015 John Wiley & Sons Ltd.

  17. Global mass spectrometry based metabolomics profiling of erythrocytes infected with Plasmodium falciparum.

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    Theodore R Sana

    data acquisition. Untargeted and targeted data mining workflows, when used together to perform pathway-inferred metabolomics, have the benefit of obviating MS/MS confirmation for every detected compound.

  18. The Guard Cell Metabolome: Functions in Stomatal Movement and Global Food Security

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    Biswapriya eMisra

    2015-05-01

    Full Text Available Guard cells represent a unique single cell-type system for the study of cellular responses to abiotic and biotic perturbations that affect stomatal movement. Decades of effort through both classical physiological and functional genomics approaches have generated an enormous amount of information on the roles of individual metabolites in stomatal guard cell function and physiology. Recent application of metabolomics methods has produced a substantial amount of new information on metabolome control of stomatal movement. In conjunction with other ‘omics’ approaches, the knowledge-base is growing to reach a systems-level description of this single cell-type. Here we summarize current knowledge of the guard cell metabolome and highlight critical metabolites that bear significant impact on future engineering and breeding efforts to generate plants/crops that are resistant to environmental challenges and produce high yield and quality products for food and energy security.

  19. The classification of almonds (Prunus dulcis) by country and variety using UHPLC-HRMS-based untargeted metabolomics.

    Science.gov (United States)

    Gil Solsona, R; Boix, C; Ibáñez, M; Sancho, J V

    2018-03-01

    The aim of this study was to use an untargeted UHPLC-HRMS-based metabolomics approach allowing discrimination between almonds based on their origin and variety. Samples were homogenised, extracted with ACN:H 2 O (80:20) containing 0.1% HCOOH and injected in a UHPLC-QTOF instrument in both positive and negative ionisation modes. Principal component analysis (PCA) was performed to ensure the absence of outliers. Partial least squares - discriminant analysis (PLS-DA) was employed to create and validate the models for country (with five different compounds) and variety (with 20 features), showing more than 95% accuracy. Additional samples were injected and the model was evaluated with blind samples, with more than 95% of samples being correctly classified using both models. MS/MS experiments were carried out to tentatively elucidate the highlighted marker compounds (pyranosides, peptides or amino acids, among others). This study has shown the potential of high-resolution mass spectrometry to perform and validate classification models, also providing information concerning the identification of the unexpected biomarkers which showed the highest discriminant power.

  20. NMR-based metabolomics for simultaneously evaluating multiple determinants of primary beef quality in Japanese Black cattle.

    Science.gov (United States)

    Kodani, Yoshinori; Miyakawa, Takuya; Komatsu, Tomohiko; Tanokura, Masaru

    2017-05-02

    Analytical methodologies to comprehensively evaluate beef quality are increasingly needed to accelerate improvement in both breeding and post-mortem processing. Consumer palatability towards beef is generally attributed to tenderness, flavor, and/or juiciness. These primary qualities are modified by post-mortem aging and the crude content and fatty acid composition of intramuscular fat. In this study, we report a nuclear magnetic resonance (NMR)-based metabolic profiles of Japanese Black cattle to evaluate the compositional attributes of intramuscular fat and the long-term post-mortem aging. The unsaturation degree of triacylglycerol was estimated by the 1 H NMR spectra and was correlated with the content ratio of unsaturated fatty acids (R 2  = 0.944) and the melting point of intramuscular fat (R 2  = 0.871). NMR-detected profiles of water-soluble metabolites revealed overall metabolic change (R 2  = 0.951) and several metabolites (R 2  > 0.818) linearly correlated with long-term aging duration, which can be used to evaluate the aging rate and aging duration of beef. This approach also provided the pH profile during aging, which is related to the water-holding capacity of beef. Thus, NMR-based metabolomics has the potential to evaluate multiple parameters related to the beef qualities of Japanese Black cattle.

  1. Toxicological effects induced by cadmium in gills of Manila clam ruditapes philippinarum using NMR-based metabolomics

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, Linbao; Liu, Xiaoli; You, Liping; Zhou, Di [Key Laboratory of Coastal Zone Environment Processes, CAS, Shandong Provincial Key Laboratory of Coastal Zone Environment Processes, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai (China); The Graduate School of Chinese Academy of Sciences, Beijing (China); Yu, Junbao; Zhao, Jianmin; Wu, Huifeng [Key Laboratory of Coastal Zone Environment Processes, CAS, Shandong Provincial Key Laboratory of Coastal Zone Environment Processes, Yantai Institute of Coastal Zone Research, Chinese Academy of Sciences, Yantai (China); Feng, Jianghua [Department of Electronic Science, Fujian Key Laboratory of Plasma and Magnetic Resonance, State Key Laboratory of Physical Chemistry of Solid Surfaces, Xiamen University, Xiamen (China)

    2011-11-15

    Cadmium (Cd) has become an important heavy metal contaminant in the sediment and seawater along the Bohai Sea and been of great ecological risk due to its toxic effects to marine organisms. In this work, the toxicological effects caused by environmentally relevant concentrations (10 and 40 {mu}g L{sup -1}) of Cd were studied in the gill tissues of Manila clam Ruditapes philippinarum after exposure for 24, 48, and 96 h. Both low (10 {mu}g L{sup -1}) and high (40 {mu}g L{sup -1}) doses of Cd caused the disturbances in energy metabolism and osmotic regulation and neurotoxicity based on the metabolic biomarkers such as succinate, alanine, branched chain amino acids, betaine, hypotaurine, and glutamate in clam gills after 24 h of exposure. However, the recovery of toxicological effects of Cd after exposure for 96 h was obviously observed in clam to Cd exposures. Overall, these results indicated that NMR-based metabolomics was applicable to elucidate the toxicological effects of heavy metal contaminants in the marine bioindicator. (Copyright copyright 2011 WILEY-VCH Verlag GmbH and Co. KGaA, Weinheim)

  2. Comparison of Chemical Compositions in Pseudostellariae Radix from Different Cultivated Fields and Germplasms by NMR-Based Metabolomics

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    Yujiao Hua

    2016-11-01

    Full Text Available Pseudostellariae Radix (PR is an important traditional Chinese medicine (TCM, which is consumed commonly for its positive health effects. However, the chemical differences of PR from different cultivated fields and germplasms are still unknown. In order to comprehensively compare the chemical compositions of PR from different cultivated fields, in this study, 1H-NMR-based metabolomics coupled with high performance liquid chromatography (HPLC were used to investigate the different metabolites in PR from five germplasms (jr, zs1, zs2, sb, and xc cultivated in traditional fields (Jurong, Jiangsu, JSJR and cultivated fields (Zherong, Fujian, FJZR. A total of 34 metabolites were identified based on 1H-NMR data, and fourteen of them were found to be different in PR from JSJR and FJZR. The relative contents of alanine, lactate, lysine, taurine, sucrose, tyrosine, linolenic acid, γ-aminobutyrate, and hyperoside in PR from JSJR were higher than that in PR from FJZR, while PR from FJZR contained higher levels of glutamine, raffinose, xylose, unsaturated fatty acid, and formic acid. The contents of Heterophyllin A and Heterophyllin B were higher in PR from FJZR. This study will provide the basic information for exploring the influence law of ecological environment and germplasm genetic variation on metabolite biosynthesis of PR and its quality formation mechanism.

  3. Sparse network modeling and metscape-based visualization methods for the analysis of large-scale metabolomics data.

    Science.gov (United States)

    Basu, Sumanta; Duren, William; Evans, Charles R; Burant, Charles F; Michailidis, George; Karnovsky, Alla

    2017-05-15

    Recent technological advances in mass spectrometry, development of richer mass spectral libraries and data processing tools have enabled large scale metabolic profiling. Biological interpretation of metabolomics studies heavily relies on knowledge-based tools that contain information about metabolic pathways. Incomplete coverage of different areas of metabolism and lack of information about non-canonical connections between metabolites limits the scope of applications of such tools. Furthermore, the presence of a large number of unknown features, which cannot be readily identified, but nonetheless can represent bona fide compounds, also considerably complicates biological interpretation of the data. Leveraging recent developments in the statistical analysis of high-dimensional data, we developed a new Debiased Sparse Partial Correlation algorithm (DSPC) for estimating partial correlation networks and implemented it as a Java-based CorrelationCalculator program. We also introduce a new version of our previously developed tool Metscape that enables building and visualization of correlation networks. We demonstrate the utility of these tools by constructing biologically relevant networks and in aiding identification of unknown compounds. http://metscape.med.umich.edu. Supplementary data are available at Bioinformatics online. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com

  4. ¹H-NMR and MS based metabolomics study of the intervention effect of curcumin on hyperlipidemia mice induced by high-fat diet.

    Science.gov (United States)

    Li, Ze-Yun; Ding, Li-Li; Li, Jin-Mei; Xu, Bao-Li; Yang, Li; Bi, Kai-Shun; Wang, Zheng-Tao

    2015-01-01

    Curcumin, a principle bioactive component of Curcuma longa L, is well known for its anti-hyperlipidemia effect. However, no holistic metabolic information of curcumin on hyperlipidemia models has been revealed, which may provide us an insight into the underlying mechanism. In the present work, NMR and MS based metabolomics was conducted to investigate the intervention effect of curcumin on hyperlipidemia mice induced by high-fat diet (HFD) feeding for 12 weeks. The HFD induced animals were orally administered with curcumin (40, 80 mg/kg) or lovastatin (30 mg/kg, positive control) once a day during the inducing period. Serum biochemistry assay of TC, TG, LDL-c, and HDL-c was conducted and proved that treatment of curcumin or lovastatin can significantly improve the lipid profiles. Subsequently, metabolomics analysis was carried out for urine samples. Orthogonal Partial Least Squares-Discriminant analysis (OPLS-DA) was employed to investigate the anti-hyperlipidemia effect of curcumin and to detect related potential biomarkers. Totally, 35 biomarkers were identified, including 31 by NMR and nine by MS (five by both). It turned out that curcumin treatment can partially recover the metabolism disorders induced by HFD, with the following metabolic pathways involved: TCA cycle, glycolysis and gluconeogenesis, synthesis of ketone bodies and cholesterol, ketogenesis of branched chain amino acid, choline metabolism, and fatty acid metabolism. Besides, NMR and MS based metabolomics proved to be powerful tools in investigating pharmacodynamics effect of natural products and underlying mechanisms.

  5. ¹H-NMR and MS based metabolomics study of the intervention effect of curcumin on hyperlipidemia mice induced by high-fat diet.

    Directory of Open Access Journals (Sweden)

    Ze-Yun Li

    Full Text Available Curcumin, a principle bioactive component of Curcuma longa L, is well known for its anti-hyperlipidemia effect. However, no holistic metabolic information of curcumin on hyperlipidemia models has been revealed, which may provide us an insight into the underlying mechanism. In the present work, NMR and MS based metabolomics was conducted to investigate the intervention effect of curcumin on hyperlipidemia mice induced by high-fat diet (HFD feeding for 12 weeks. The HFD induced animals were orally administered with curcumin (40, 80 mg/kg or lovastatin (30 mg/kg, positive control once a day during the inducing period. Serum biochemistry assay of TC, TG, LDL-c, and HDL-c was conducted and proved that treatment of curcumin or lovastatin can significantly improve the lipid profiles. Subsequently, metabolomics analysis was carried out for urine samples. Orthogonal Partial Least Squares-Discriminant analysis (OPLS-DA was employed to investigate the anti-hyperlipidemia effect of curcumin and to detect related potential biomarkers. Totally, 35 biomarkers were identified, including 31 by NMR and nine by MS (five by both. It turned out that curcumin treatment can partially recover the metabolism disorders induced by HFD, with the following metabolic pathways involved: TCA cycle, glycolysis and gluconeogenesis, synthesis of ketone bodies and cholesterol, ketogenesis of branched chain amino acid, choline metabolism, and fatty acid metabolism. Besides, NMR and MS based metabolomics proved to be powerful tools in investigating pharmacodynamics effect of natural products and underlying mechanisms.

  6. Identification of Altered Metabolomic Profiles Following a Panchakarma-based Ayurvedic Intervention in Healthy Subjects: The Self-Directed Biological Transformation Initiative (SBTI).

    Science.gov (United States)

    Peterson, Christine Tara; Lucas, Joseph; John-Williams, Lisa St; Thompson, J Will; Moseley, M Arthur; Patel, Sheila; Peterson, Scott N; Porter, Valencia; Schadt, Eric E; Mills, Paul J; Tanzi, Rudolph E; Doraiswamy, P Murali; Chopra, Deepak

    2016-09-09

    The effects of integrative medicine practices such as meditation and Ayurveda on human physiology are not fully understood. The aim of this study was to identify altered metabolomic profiles following an Ayurveda-based intervention. In the experimental group, 65 healthy male and female subjects participated in a 6-day Panchakarma-based Ayurvedic intervention which included herbs, vegetarian diet, meditation, yoga, and massage. A set of 12 plasma phosphatidylcholines decreased (adjusted p < 0.01) post-intervention in the experimental (n = 65) compared to control group (n = 54) after Bonferroni correction for multiple testing; within these compounds, the phosphatidylcholine with the greatest decrease in abundance was PC ae C36:4 (delta = -0.34). Application of a 10% FDR revealed an additional 57 metabolites that were differentially abundant between groups. Pathway analysis suggests that the intervention results in changes in metabolites across many pathways such as phospholipid biosynthesis, choline metabolism, and lipoprotein metabolism. The observed plasma metabolomic alterations may reflect a Panchakarma-induced modulation of metabotypes. Panchakarma promoted statistically significant changes in plasma levels of phosphatidylcholines, sphingomyelins and others in just 6 days. Forthcoming studies that integrate metabolomics with genomic, microbiome and physiological parameters may facilitate a broader systems-level understanding and mechanistic insights into these integrative practices that are employed to promote health and well-being.

  7. Feasibility Study of NMR Based Serum Metabolomic Profiling to Animal Health Monitoring: A Case Study on Iron Storage Disease in Captive Sumatran Rhinoceros (Dicerorhinus sumatrensis.

    Directory of Open Access Journals (Sweden)

    Miki Watanabe

    Full Text Available A variety of wildlife species maintained in captivity are susceptible to iron storage disease (ISD, or hemochromatosis, a disease resulting from the deposition of excess iron into insoluble iron clusters in soft tissue. Sumatran rhinoceros (Dicerorhinus sumatrensis is one of the rhinoceros species that has evolutionarily adapted to a low-iron diet and is susceptible to iron overload. Hemosiderosis is reported at necropsy in many African black and Sumatran rhinoceroses but only a small number of animals reportedly die from hemochromatosis. The underlying cause and reasons for differences in susceptibility to hemochromatosis within the taxon remains unclear. Although serum ferritin concentrations have been useful in monitoring the progression of ISD in many species, there is some question regarding their value in diagnosing hemochromatosis in the Sumatran rhino. To investigate the metabolic changes during the development of hemochromatosis and possibly increase our understanding of its progression and individual susceptibility differences, the serum metabolome from a Sumatran rhinoceros was investigated by nuclear magnetic resonance (NMR-based metabolomics. The study involved samples from female rhinoceros at the Cincinnati Zoo (n = 3, including two animals that died from liver failure caused by ISD, and the Sungai Dusun Rhinoceros Conservation Centre in Peninsular Malaysia (n = 4. Principal component analysis was performed to visually and statistically compare the metabolic profiles of the healthy animals. The results indicated that significant differences were present between the animals at the zoo and the animals in the conservation center. A comparison of the 43 serum metabolomes of three zoo rhinoceros showed two distinct groupings, healthy (n = 30 and unhealthy (n = 13. A total of eighteen altered metabolites were identified in healthy versus unhealthy samples. Results strongly suggest that NMR-based metabolomics is a valuable tool for

  8. Feasibility Study of NMR Based Serum Metabolomic Profiling to Animal Health Monitoring: A Case Study on Iron Storage Disease in Captive Sumatran Rhinoceros (Dicerorhinus sumatrensis)

    Science.gov (United States)

    Watanabe, Miki; Roth, Terri L.; Bauer, Stuart J.; Lane, Adam; Romick-Rosendale, Lindsey E.

    2016-01-01

    A variety of wildlife species maintained in captivity are susceptible to iron storage disease (ISD), or hemochromatosis, a disease resulting from the deposition of excess iron into insoluble iron clusters in soft tissue. Sumatran rhinoceros (Dicerorhinus sumatrensis) is one of the rhinoceros species that has evolutionarily adapted to a low-iron diet and is susceptible to iron overload. Hemosiderosis is reported at necropsy in many African black and Sumatran rhinoceroses but only a small number of animals reportedly die from hemochromatosis. The underlying cause and reasons for differences in susceptibility to hemochromatosis within the taxon remains unclear. Although serum ferritin concentrations have been useful in monitoring the progression of ISD in many species, there is some question regarding their value in diagnosing hemochromatosis in the Sumatran rhino. To investigate the metabolic changes during the development of hemochromatosis and possibly increase our understanding of its progression and individual susceptibility differences, the serum metabolome from a Sumatran rhinoceros was investigated by nuclear magnetic resonance (NMR)-based metabolomics. The study involved samples from female rhinoceros at the Cincinnati Zoo (n = 3), including two animals that died from liver failure caused by ISD, and the Sungai Dusun Rhinoceros Conservation Centre in Peninsular Malaysia (n = 4). Principal component analysis was performed to visually and statistically compare the metabolic profiles of the healthy animals. The results indicated that significant differences were present between the animals at the zoo and the animals in the conservation center. A comparison of the 43 serum metabolomes of three zoo rhinoceros showed two distinct groupings, healthy (n = 30) and unhealthy (n = 13). A total of eighteen altered metabolites were identified in healthy versus unhealthy samples. Results strongly suggest that NMR-based metabolomics is a valuable tool for animal health

  9. Probabilistic Principal Component Analysis for Metabolomic Data.

    LENUS (Irish Health Repository)

    Nyamundanda, Gift

    2010-11-23

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

  10. Metabolomics-based chemotaxonomy of root endophytic fungi for natural products discovery.

    Science.gov (United States)

    Maciá-Vicente, Jose G; Shi, Yan-Ni; Cheikh-Ali, Zakaria; Grün, Peter; Glynou, Kyriaki; Kia, Sevda Haghi; Piepenbring, Meike; Bode, Helge B

    2018-03-01

    Fungi are prolific producers of natural products routinely screened for biotechnological applications, and those living endophytically within plants attract particular attention because of their purported chemical diversity. However, the harnessing of their biosynthetic potential is hampered by a large and often cryptic phylogenetic and ecological diversity, coupled with a lack of large-scale natural products' dereplication studies. To guide efforts to discover new chemistries among root-endophytic fungi, we analyzed the natural products produced by 822 strains using an untargeted UPLC-ESI-MS/MS-based approach and linked the patterns of chemical features to fungal lineages. We detected 17 809 compounds of which 7951 were classified in 1992 molecular families, whereas the remaining were considered unique chemistries. Our approach allowed to annotate 1191 compounds with different degrees of accuracy, many of which had known fungal origins. Approximately 61% of the compounds were specific of a fungal order, and differences were observed across lineages in the diversity and characteristics of their chemistries. Chemical profiles also showed variable chemosystematic values across lineages, ranging from relative homogeneity to high heterogeneity among related fungi. Our results provide an extensive resource to dereplicate fungal natural products and may assist future discovery programs by providing a guide for the selection of target fungi. © 2018 Society for Applied Microbiology and John Wiley & Sons Ltd.

  11. High Resolution UHPLC-MS Metabolomics and Sedative-Anxiolytic Effects of Latua pubiflora: A Mystic Plant used by Mapuche Amerindians.

    Science.gov (United States)

    Sánchez-Montoya, Eliana L; Reyes, Marco A; Pardo, Joel; Nuñez-Alarcón, Juana; Ortiz, José G; Jorge, Juan C; Bórquez, Jorge; Mocan, Andrei; Simirgiotis, Mario J

    2017-01-01

    Latua pubiflora (Griseb) Phil. Is a native shrub of the Solanaceae family that grows freely in southern Chile and is employed among Mapuche aboriginals to induce sedative effects and hallucinations in religious or medicine rituals since prehispanic times. In this work, the pentobarbital-induced sleeping test and the elevated plus maze test were employed to test the behavioral effects of extracts of this plant in mice. The psychopharmacological evaluation of L. pubiflora extracts in mice determined that both alkaloid-enriched as well as the non-alkaloid extracts produced an increase of sleeping time and alteration of motor activity in mice at 150 mg/Kg. The alkaloid extract exhibited anxiolytic effects in the elevated plus maze test, which was counteracted by flumazenil. In addition, the alkaloid extract from L. pubiflora decreased [ 3 H]-flunitrazepam binding on rat cortical membranes. In this study we have identified 18 tropane alkaloids (peaks 1-4, 8-13, 15-18, 21, 23, 24, and 28), 8 phenolic acids and related compounds (peaks 5-7, 14, 19, 20, 22, and 29) and 7 flavonoids (peaks 25-27 and 30-33) in extracts of L. pubiflora by UHPLC-PDA-MS which are responsible for the biological activity. This study assessed for the first time the sedative-anxiolytic effects of L. pubiflora in rats besides the high resolution metabolomics analysis including the finding of pharmacologically important tropane alkaloids and glycosylated flavonoids.

  12. Metabolite profiling, antioxidant, and α-glucosidase inhibitory activities of germinated rice: nuclear-magnetic-resonance-based metabolomics study

    Directory of Open Access Journals (Sweden)

    Phaiwan Pramai

    2018-01-01

    Full Text Available In an attempt to profile the metabolites of three different varieties of germinated rice, specifically black (GBR, red, and white rice, a 1H-nuclear-magnetic-resonance-based metabolomics approach was conducted. Multivariate data analysis was applied to discriminate between the three different varieties using a partial least squares discriminant analysis (PLS-DA model. The PLS model was used to evaluate the relationship between chemicals and biological activities of germinated rice. The PLS-DA score plot exhibited a noticeable separation between the three rice varieties into three clusters by PC1 and PC2. The PLS model indicated that α-linolenic acid, γ-oryzanol, α-tocopherol, γ-aminobutyric acid, 3-hydroxybutyric acid, fumaric acid, fatty acids, threonine, tryptophan, and vanillic acid were significantly correlated with the higher bioactivities demonstrated by GBR that was extracted in 100% ethanol. Subsequently, the proposed biosynthetic pathway analysis revealed that the increased quantities of secondary metabolites found in GBR may contribute to its nutritional value and health benefits.

  13. Metabolite profiling, antioxidant, and α-glucosidase inhibitory activities of germinated rice: nuclear-magnetic-resonance-based metabolomics study.

    Science.gov (United States)

    Pramai, Phaiwan; Abdul Hamid, Nur Ashikin; Mediani, Ahmed; Maulidiani, Maulidiani; Abas, Faridah; Jiamyangyuen, Sudarat

    2018-01-01

    In an attempt to profile the metabolites of three different varieties of germinated rice, specifically black (GBR), red, and white rice, a 1 H-nuclear-magnetic-resonance-based metabolomics approach was conducted. Multivariate data analysis was applied to discriminate between the three different varieties using a partial least squares discriminant analysis (PLS-DA) model. The PLS model was used to evaluate the relationship between chemicals and biological activities of germinated rice. The PLS-DA score plot exhibited a noticeable separation between the three rice varieties into three clusters by PC1 and PC2. The PLS model indicated that α-linolenic acid, γ-oryzanol, α-tocopherol, γ-aminobutyric acid, 3-hydroxybutyric acid, fumaric acid, fatty acids, threonine, tryptophan, and vanillic acid were significantly correlated with the higher bioactivities demonstrated by GBR that was extracted in 100% ethanol. Subsequently, the proposed biosynthetic pathway analysis revealed that the increased quantities of secondary metabolites found in GBR may contribute to its nutritional value and health benefits. Copyright © 2017. Published by Elsevier B.V.

  14. Nephron Toxicity Profiling via Untargeted Metabolome Analysis Employing a High Performance Liquid Chromatography-Mass Spectrometry-based Experimental and Computational Pipeline.

    Science.gov (United States)

    Ranninger, Christina; Rurik, Marc; Limonciel, Alice; Ruzek, Silke; Reischl, Roland; Wilmes, Anja; Jennings, Paul; Hewitt, Philip; Dekant, Wolfgang; Kohlbacher, Oliver; Huber, Christian G

    2015-07-31

    Untargeted metabolomics has the potential to improve the predictivity of in vitro toxicity models and therefore may aid the replacement of expensive and laborious animal models. Here we describe a long term repeat dose nephrotoxicity study conducted on the human renal proximal tubular epithelial cell line, RPTEC/TERT1, treated with 10 and 35 μmol·liter(-1) of chloroacetaldehyde, a metabolite of the anti-cancer drug ifosfamide. Our study outlines the establishment of an automated and easy to use untargeted metabolomics workflow for HPLC-high resolution mass spectrometry data. Automated data analysis workflows based on open source software (OpenMS, KNIME) enabled a comprehensive and reproducible analysis of the complex and voluminous metabolomics data produced by the profiling approach. Time- and concentration-dependent responses were clearly evident in the metabolomic profiles. To obtain a more comprehensive picture of the mode of action, transcriptomics and proteomics data were also integrated. For toxicity profiling of chloroacetaldehyde, 428 and 317 metabolite features were detectable in positive and negative modes, respectively, after stringent removal of chemical noise and unstable signals. Changes upon treatment were explored using principal component analysis, and statistically significant differences were identified using linear models for microarray assays. The analysis revealed toxic effects only for the treatment with 35 μmol·liter(-1) for 3 and 14 days. The most regulated metabolites were glutathione and metabolites related to the oxidative stress response of the cells. These findings are corroborated by proteomics and transcriptomics data, which show, among other things, an activation of the Nrf2 and ATF4 pathways. © 2015 by The American Society for Biochemistry and Molecular Biology, Inc.

  15. Untargeted metabolomics: an emerging approach to determine the composition of herbal products

    Directory of Open Access Journals (Sweden)

    Flavia Guzzo

    2013-01-01

    Full Text Available Natural remedies, such as those based on traditional Chinese medicines, have become more popular also in western countries over the last 10 years. The composition of these herbal products is largely unknown and difficult to determine. Moreover, since plants respond to their environment changing the metabolome, the composition of plant material can vary depending on the plant growth conditions.However, there is a growing need of a deeper knowledge on such natural remedies also in view of the growing number of reports of toxicity following the consumption of herbal supplements. Untargeted metabolomics is a useful approach for the simultaneous analysis of many compounds in herbal products. In particular, liquid chromatography/mass spectrometry (LC-MS can determine presence, amount and sometime structures of plant metabolites in complex herbal mixtures, with significant advantages over techniques such as nuclear magnetic resonance (NMR spectroscopy and gas chromatography/mass spectrometry (GC-MS.

  16. Plant iTRAQ-based proteomics

    Energy Technology Data Exchange (ETDEWEB)

    Handakumbura, Pubudu; Hixson, Kim K.; Purvine, Samuel O.; Jansson, Georg C.; Pasa Tolic, Ljiljana

    2017-06-21

    We present a simple one-­pot extraction protocol, which rapidly isolates hydrophyllic metabolites, lipids, and proteins from the same pulverized plant sample. Also detailed is a global plant proteomics sample preparation method utilizing iTRAQ multiplexing reagents that enables deep proteome coverage due to the use of HPLC fractionation of the peptides prior to mass spectrometric analysis. We have successfully used this protocol on several different plant tissues (e.g., roots, stems, leaves) from different plants (e.g., sorghum, poplar, Arabidopsis, soybean), and have been able to successfully detect and quantify thousands of proteins. Multiplexing strategies such as iTRAQ and the bioinformatics strategy outlined here, ultimately provide insight into which proteins are significantly changed in abundance between two or more groups (e.g., control, perturbation). Our bioinformatics strategy yields z-­score values, which normalize the expression data into a format that can easily be cross-­compared with other expression data (i.e., metabolomics, transcriptomics) obtained from different analytical methods and instrumentation.

  17. Cell-based metabolomics for assessing chemical exposure and toxicity of environmental surface waters (presentation)

    Science.gov (United States)

    Introduction: Waste water treatment plants (WWTPs), concentrated animal feeding operations (CAFOs), mining activities, and agricultural operations release contaminants that negatively affect surface water quality. Traditional methods using live animals (e.g. fish) to monitor/as...

  18. Cell-based Metabolomics for Assessing Chemical Exposure and Toxicity of Environmental Surface Waters

    Science.gov (United States)

    Waste water treatment plants (WWTPs), concentrated animal feeding operations (CAFOs), mining activities, and agricultural operations release contaminants that negatively affect surface water quality. Traditional methods using live animals/fish to monitor/assess contaminant exposu...

  19. Vitamins, metabolomics, and prostate cancer.

    Science.gov (United States)

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

    2017-06-01

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

  20. Metabolomic Studies in Drosophila.

    Science.gov (United States)

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

    2017-07-01

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

  1. Transcriptomic and metabolomic analysis of Yukon Thellungiella plants grown in cabinets and their natural habitat show phenotypic plasticity

    Directory of Open Access Journals (Sweden)

    Guevara David R

    2012-10-01

    Full Text Available Abstract Background Thellungiella salsuginea is an important model plant due to its natural tolerance to abiotic stresses including salt, cold, and water deficits. Microarray and metabolite profiling have shown that Thellungiella undergoes stress-responsive changes in transcript and organic solute abundance when grown under controlled environmental conditions. However, few reports assess the capacity of plants to display stress-responsive traits in natural habitats where concurrent stresses are the norm. Results To determine whether stress-responsive changes observed in cabinet-grown plants are recapitulated in the field, we analyzed leaf transcript and metabolic profiles of Thellungiella growing in its native Yukon habitat during two years of contrasting meteorological conditions. We found 673 genes showing differential expression between field and unstressed, chamber-grown plants. There were comparatively few overlaps between genes expressed under field and cabinet treatment-specific conditions. Only 20 of 99 drought-responsive genes were expressed both in the field during a year of low precipitation and in plants subjected to drought treatments in cabinets. There was also a general pattern of lower abundance among metabolites found in field plants relative to control or stress-treated plants in growth cabinets. Nutrient availability may explain some of the observed differences. For example, proline accumulated to high levels in cold and salt-stressed cabinet-grown plants but proline content was, by comparison, negligible in plants at a saline Yukon field site. We show that proline accumulated in a stress-responsive manner in Thellungiella plants salinized in growth cabinets and in salt-stressed seedlings when nitrogen was provided at 1.0 mM. In seedlings grown on 0.1 mM nitrogen medium, the proline content was low while carbohydrates increased. The relatively higher content of sugar-like compounds in field plants and seedlings on low nitrogen

  2. Transcriptomic and metabolomic analysis of Yukon Thellungiella plants grown in cabinets and their natural habitat show phenotypic plasticity.

    Science.gov (United States)

    Guevara, David R; Champigny, Marc J; Tattersall, Ashley; Dedrick, Jeff; Wong, Chui E; Li, Yong; Labbe, Aurelie; Ping, Chien-Lu; Wang, Yanxiang; Nuin, Paulo; Golding, G Brian; McCarry, Brian E; Summers, Peter S; Moffatt, Barbara A; Weretilnyk, Elizabeth A

    2012-10-01

    Thellungiella salsuginea is an important model plant due to its natural tolerance to abiotic stresses including salt, cold, and water deficits. Microarray and metabolite profiling have shown that Thellungiella undergoes stress-responsive changes in transcript and organic solute abundance when grown under controlled environmental conditions. However, few reports assess the capacity of plants to display stress-responsive traits in natural habitats where concurrent stresses are the norm. To determine whether stress-responsive changes observed in cabinet-grown plants are recapitulated in the field, we analyzed leaf transcript and metabolic profiles of Thellungiella growing in its native Yukon habitat during two years of contrasting meteorological conditions. We found 673 genes showing differential expression between field and unstressed, chamber-grown plants. There were comparatively few overlaps between genes expressed under field and cabinet treatment-specific conditions. Only 20 of 99 drought-responsive genes were expressed both in the field during a year of low precipitation and in plants subjected to drought treatments in cabinets. There was also a general pattern of lower abundance among metabolites found in field plants relative to control or stress-treated plants in growth cabinets. Nutrient availability may explain some of the observed differences. For example, proline accumulated to high levels in cold and salt-stressed cabinet-grown plants but proline content was, by comparison, negligible in plants at a saline Yukon field site. We show that proline accumulated in a stress-responsive manner in Thellungiella plants salinized in growth cabinets and in salt-stressed seedlings when nitrogen was provided at 1.0 mM. In seedlings grown on 0.1 mM nitrogen medium, the proline content was low while carbohydrates increased. The relatively higher content of sugar-like compounds in field plants and seedlings on low nitrogen media suggests that Thellungiella shows

  3. Transcriptomic and metabolomic analysis of Yukon Thellungiella plants grown in cabinets and their natural habitat show phenotypic plasticity

    Science.gov (United States)

    2012-01-01

    Background Thellungiella salsuginea is an important model plant due to its natural tolerance to abiotic stresses including salt, cold, and water deficits. Microarray and metabolite profiling have shown that Thellungiella undergoes stress-responsive changes in transcript and organic solute abundance when grown under controlled environmental conditions. However, few reports assess the capacity of plants to display stress-responsive traits in natural habitats where concurrent stresses are the norm. Results To determine whether stress-responsive changes observed in cabinet-grown plants are recapitulated in the field, we analyzed leaf transcript and metabolic profiles of Thellungiella growing in its native Yukon habitat during two years of contrasting meteorological conditions. We found 673 genes showing differential expression between field and unstressed, chamber-grown plants. There were comparatively few overlaps between genes expressed under field and cabinet treatment-specific conditions. Only 20 of 99 drought-responsive genes were expressed both in the field during a year of low precipitation and in plants subjected to drought treatments in cabinets. There was also a general pattern of lower abundance among metabolites found in field plants relative to control or stress-treated plants in growth cabinets. Nutrient availability may explain some of the observed differences. For example, proline accumulated to high levels in cold and salt-stressed cabinet-grown plants but proline content was, by comparison, negligible in plants at a saline Yukon field site. We show that proline accumulated in a stress-responsive manner in Thellungiella plants salinized in growth cabinets and in salt-stressed seedlings when nitrogen was provided at 1.0 mM. In seedlings grown on 0.1 mM nitrogen medium, the proline content was low while carbohydrates increased. The relatively higher content of sugar-like compounds in field plants and seedlings on low nitrogen media suggests that

  4. Comparative UPLC-QTOF-MS-based metabolomics and bioactivities analyses of Garcinia oblongifolia.

    Science.gov (United States)

    Li, Ping; AnandhiSenthilkumar, Harini; Wu, Shi-biao; Liu, Bo; Guo, Zhi-yong; Fata, Jimmie E; Kennelly, Edward J; Long, Chun-lin

    2016-02-01

    Garcinia oblongifolia Champ. ex Benth. (Clusiaceae) is a well-known medicinal plant from southern China, with edible fruits. However, the phytochemistry and bioactivity of the different plant parts of G. oblongifolia have not been studied extensively. Comparative metabolic profiling and bioactivities of the leaf, branch, and fruit of G. oblongifolia were investigated. A total of 40 compounds such as biflavonoids, xanthones, and benzophenones were identified using UPLC-QTOF-MS and MS(E), including 15 compounds reported for the first time from this species. Heatmap analyses found that benzophenones, xanthones, and biflavonoids were predominately found in branches, with benzophenones present in relatively high concentrations in all three plant parts. Xanthones were found to have limited distribution in fruit while biflavonoids were present at only low levels in leaves. In addition, the cytotoxic (MCF-7 breast cancer cell line) and antioxidant (ABTS and DPPH chemical tests) activities of the crude extracts of G. oblongifolia indicate that the branch extract exhibits greater bioactivity than either the leaf or the fruit extracts. Orthogonal partial least squares discriminate analysis was used to find 12 marker compounds, mainly xanthones, from the branches, including well-known antioxidants and cytotoxic agents. These G. oblongifolia results revealed that the variation in metabolite profiles can be correlated to the differences in bioactivity of the three plant parts investigated. This UPLC-QTOF-MS strategy can be useful to identify bioactive constituents expressed differentially in the various plant parts of a single species. Copyright © 2016 Elsevier B.V. All rights reserved.

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

    International Nuclear Information System (INIS)

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

    2016-01-01

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

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2016-07-13

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

  7. NMR-based metabolomics and hyphenated NMR techniques – a perfect match in natural products research

    DEFF Research Database (Denmark)

    Vinther, Joachim Møllesøe; Wubshet, Sileshi Gizachew; Stærk, Dan

    2015-01-01

    Ethnopharmacology is one of the world’s fastest-growing scientific disciplines encompassing a diverse range of subjects. It links natural sciences research on medicinal, aromatic and toxic plants with socio-cultural studies and has often been associated with the development of new drugs...

  8. NMR-based Metabolomics Analysis of Liver from C57BL/6 Mouse Exposed to Ionizing Radiation

    Energy Technology Data Exchange (ETDEWEB)

    Xiao, Xiongjie [Pacific Northwest National Laboratory, Richland, Washington 99352; State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, the Chinese Academy of Sciences, Wuhan, 430071, PR China; University of Chinese Academy of Sciences, Beijing 100049, China; Hu, Mary [Pacific Northwest National Laboratory, Richland, Washington 99352; Zhang, Xu [State Key Laboratory of Magnetic Resonance and Atomic and Molecular Physics, National Center for Magnetic Resonance in Wuhan, Wuhan Institute of Physics and Mathematics, the Chinese Academy of Sciences, Wuhan, 430071, PR China; Hu, Jian Zhi [Pacific Northwest National Laboratory, Richland, Washington 99352

    2017-07-01

    The health effects of exposing to ionizing radiation are attracting great interest in the space exploration community and patients considering radiotherapy. However, the impact to metabolism after exposure to high dose radiation has not yet been clearly defined in livers. In the present study, 1H nuclear magnetic resonance (NMR) based metabolomics combined with multivariate data analysis are applied to study the changes of metabolism in the liver of C57BL/6 mouse after whole body exposure to either gamma (3.0 and 7.8 Gy) or proton (3.0 Gy) radiation. Principal component analysis (PCA) and orthogonal projection to latent structures analysis (OPLS) are employed for classification and identification of potential biomarkers associated with gamma and proton irradiation. The results show that the radiation exposed groups can be well separated from the control group. At the same radiation dosage, the group exposed to proton radiation is well separated from the group exposed to gamma radiation, indicating different radiation sources induce different alterations based on metabolic profiling. Common to both gamma and proton radiation at the high radiation doses studied in this work, compared with the control groups the concentrations of choline, O-phosphocholine and trimethylamine N-oxide are decreased statistically, while those of glutamine, glutathione, malate, creatinine, phosphate, betaine and 4-hydroxyphenylacetate are statistically and significantly elevated after exposure to radiation. Since these altered metabolites are associated with multiple biological pathways, the changes suggest that the exposure to radiation induce abnormality in multiple biological pathways. In particular, metabolites such as 4-hydroxyphenylacetate, betaine, glutamine, choline and trimethylamine N-oxide may be good candidates of pre-diagnose biomarkers for ionizing radiation in liver.

  9. 1H NMR-based serum metabolomics reveals erythromycin-induced liver toxicity in albino Wistar rats

    Directory of Open Access Journals (Sweden)

    Atul Rawat

    2016-01-01

    Full Text Available Introduction: Erythromycin (ERY is known to induce hepatic toxicity which mimics other liver diseases. Thus, ERY is often used to produce experimental models of drug-induced liver-toxicity. The serum metabolic profiles can be used to evaluate the liver-toxicity and to further improve the understanding of underlying mechanism. Objective: To establish the serum metabolic patterns of Erythromycin induced hepatotoxicity in albino wistar rats using 1H NMR based serum metabolomics. Experimental: Fourteen male rats were randomly divided into two groups (n = 7 in each group: control and ERY treated. After 28 days of intervention, the metabolic profiles of sera obtained from ERY and control groups were analyzed using high-resolution 1D 1H CPMG and diffusion-edited nuclear magnetic resonance (NMR spectra. The histopathological and SEM examinations were employed to evaluate the liver toxicity in ERY treated group. Results: The serum metabolic profiles of control and ERY treated rats were compared using multivariate statistical analysis and the metabolic patterns specific to ERY-induced liver toxicity were established. The toxic response of ERY was characterized with: (a increased serum levels of Glucose, glutamine, dimethylamine, malonate, choline, phosphocholine and phospholipids and (b decreased levels of isoleucine, leucine, valine, alanine, glutamate, citrate, glycerol, lactate, threonine, circulating lipoproteins, N-acetyl glycoproteins, and poly-unsaturated lipids. These metabolic alterations were found to be associated with (a decreased TCA cycle activity and enhanced fatty acid oxidation, (b dysfunction of lipid and amino acid metabolism and (c oxidative stress. Conclusion and Recommendations: Erythromycin is often used to produce experimental models of liver toxicity; therefore, the established NMR-based metabolic patterns will form the basis for future studies aiming to evaluate the efficacy of anti-hepatotoxic agents or the hepatotoxicity of new

  10. Twins labeling-liquid chromatography/mass spectrometry based metabolomics for absolute quantification of tryptophan and its key metabolites.

    Science.gov (United States)

    Guo, Huimin; Jiao, Yu; Wang, Xu; Lu, Tao; Zhang, Zunjian; Xu, Fengguo

    2017-06-30

    Tryptophan metabolism plays a crucial role in mediating gastrointestinal function. Here, in order to absolutely quantify tryptophan and its metabolites, a liquid chromatography-mass spectrometry (LC-MS) based targeted metabolomics approach was developed using N-dimethyl-/N-diethyl-amino naphthalene-1-sulfonyl chloride (Dns/Dens-Cl) as twins labeling (TL) reagents. Dns-Cl is famous in amine and phenol derivations, and structure is similar with Dens-Cl. The introduction of easily protonated moiety of tertiary ammonium-containing part in the derivatives from Dns to tryptophan and its metabolites not only improved the LC separation but also enhanced their MS response. In addition, the Dens labeled standards were used as internal standards to compensate for matrix effects and ensure accurate quantifications. With the proposed method, twelve metabolites in tryptophan pathway could be detected at sub-ng/mL levels using only 20μL rat serum (the limit of detection could reach 3pg/mL for tryptamine, N-acetyl-serotonin and 6-hydroxymelatonin). The sensitivity was enhanced about 1-2 orders of magnitude compared with non-derivatization method. Focusing on tryptophan pathway, the method was successfully applied to determine the absolute serum concentrations of twelve tryptophan metabolites in a vincristine-induced ileus rat model. A significant down-regulation of the tryptophan metabolism along the kynurenine pathway and up-regulation of serotonin pathway were uncovered. Our findings provide a deeper insight into the mechanism of gastrointestinal dysfunction. Copyright © 2017 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

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

    2014-01-01

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

  12. Gas chromatography/mass spectrometry-based urine metabolome study in children for inborn errors of metabolism: An Indian experience.

    Science.gov (United States)

    Hampe, Mahesh H; Panaskar, Shrimant N; Yadav, Ashwini A; Ingale, Pramod W

    2017-02-01

    The present study highlights the feasibility of gas chromatography/mass spectrometry (GC/MS)-based analysis for simultaneous detection of >200 marker metabolites in urine found in characteristic pattern in inborn errors of metabolism (IEM) in India. During this retrospective study conducted from July 2013 to January 2016, we collected urine specimens on filter papers from Indian children across the country along with relevant demographic and clinical data. The laboratory technique involved urease pretreatment followed by deproteinization, derivatization, and subsequent computer-aided analysis of organic acids, amino acids, fatty acids, and sugars by GC/MS, which enable chemical diagnosis of IEM. Totally 23,140 patients were investigated for IEM with an estimated frequency of about 1.40%, that is, 323 positive cases. Most frequent disorders observed were of primary lactic acidemia (27.2%) and organic acidemia (methylmalonic aciduria, glutaric acidemia type I, propionic aciduria, etc.) followed by aminoacidopathies (maple syrup urine disease, phenylketonuria, tyrosinemia, etc.). Furthermore, alkaptonuria, canavan disease, and 4-hydroxybutyric aciduria were also diagnosed. Prompt treatment following diagnosis led to a better outcome in a considerable number of patients. GC/MS with one-step metabolomics enables quick detection, accurate identification, and precise quantification of a wide range of urinary markers that may not be discovered using existing newborn screening programs. The technique is effective as a second-tier test to other established screening technologies, as well as one-step primary screening tool for a wide spectrum of IEM. Copyright © 2016 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

  13. The Time Is Right to Focus on Model Organism Metabolomes.

    Science.gov (United States)

    Edison, Arthur S; Hall, Robert D; Junot, Christophe; Karp, Peter D; Kurland, Irwin J; Mistrik, Robert; Reed, Laura K; Saito, Kazuki; Salek, Reza M; Steinbeck, Christoph; Sumner, Lloyd W; Viant, Mark R

    2016-02-15

    Model organisms are an essential component of biological and biomedical research that can be used to study specific biological processes. These organisms are in part selected for facile experimental study. However, just as importantly, intensive study of a small number of model organisms yields important synergies as discoveries in one area of science for a given organism shed light on biological processes in other areas, even for other organisms. Furthermore, the extensive knowledge bases compiled for each model organism enable systems-level understandings of these species, which enhance the overall biological and biomedical knowledge for all organisms, including humans. Building upon extensive genomics research, we argue that the time is now right to focus intensively on model organism metabolomes. We propose a grand challenge for metabolomics studies of model organisms: to identify and map all metabolites onto metabolic pathways, to develop quantitative metabolic models for model organisms, and to relate organism metabolic pathways within the context of evolutionary metabolomics, i.e., phylometabolomics. These efforts should focus on a series of established model organisms in microbial, animal and plant research.

  14. The Time Is Right to Focus on Model Organism Metabolomes

    Directory of Open Access Journals (Sweden)

    Arthur S. Edison

    2016-02-01

    Full Text Available Model organisms are an essential component of biological and biomedical research that can be used to study specific biological processes. These organisms are in part selected for facile experimental study. However, just as importantly, intensive study of a small number of model organisms yields important synergies as discoveries in one area of science for a given organism shed light on biological processes in other areas, even for other organisms. Furthermore, the extensive knowledge bases compiled for each model organism enable systems-level understandings of these species, which enhance the overall biological and biomedical knowledge for all organisms, including humans. Building upon extensive genomics research, we argue that the time is now right to focus intensively on model organism metabolomes. We propose a grand challenge for metabolomics studies of model organisms: to identify and map all metabolites onto metabolic pathways, to develop quantitative metabolic models for model organisms, and to relate organism metabolic pathways within the context of evolutionary metabolomics, i.e., phylometabolomics. These efforts should focus on a series of established model organisms in microbial, animal and plant research.

  15. Interactions between the jasmonic and salicylic acid pathway modulate the plant metabolome and affect herbivores of different feeding types.

    Science.gov (United States)

    Schweiger, R; Heise, A-M; Persicke, M; Müller, C

    2014-07-01

    The phytohormones jasmonic acid (JA) and salicylic acid (SA) mediate induced plant defences and the corresponding pathways interact in a complex manner as has been shown on the transcript and proteine level. Downstream, metabolic changes are important for plant-herbivore interactions. This study investigated metabolic changes in leaf tissue and phloem exudates of Plantago lanceolata after single and combined JA and SA applications as well as consequences on chewing-biting (Heliothis virescens) and piercing-sucking (Myzus persicae) herbivores. Targeted metabolite profiling and untargeted metabolic fingerprinting uncovered different categories of plant metabolites, which were influenced in a specific manner, indicating points of divergence, convergence, positive crosstalk and pronounced mutual antagonism between the signaling pathways. Phytohormone-specific decreases of primary metabolite pool sizes in the phloem exudates may indicate shifts in sink-source relations, resource allocation, nutrient uptake or photosynthesis. Survival of both herbivore species was significantly reduced by JA and SA treatments. However, the combined application of JA and SA attenuated the negative effects at least against H. virescens suggesting that mutual antagonism between the JA and SA pathway may be responsible. Pathway interactions provide a great regulatory potential for the plant that allows triggering of appropriate defences when attacked by different antagonist species. © 2013 John Wiley & Sons Ltd.

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

    Science.gov (United States)

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

    2017-09-26

    The Metabolomics Standards Initiative (MSI) guidelines were first published in 2007. These guidelines provided reporting standards for all stages of metabolomics analysis: experimental design, biological context, chemical analysis and data processing. Since 2012, a series of public metabolomics databases and repositories, which accept the deposition of metabolomic datasets, have arisen. In this study, the compliance of 399 public data sets, from four major metabolomics data repositories, to the biological context MSI reporting standards was evaluated. None of the reporting standards were complied with in every publicly available study, although adherence rates varied greatly, from 0 to 97%. The plant minimum reporting standards were the most complied with and the microbial and in vitro were the least. Our results indicate the need for reassessment and revision of the existing MSI reporting standards.

  17. New approaches for metabolomics by mass spectrometry

    Energy Technology Data Exchange (ETDEWEB)

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

    2017-07-10

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

  18. Metabolomics in chemical ecology.

    Science.gov (United States)

    Kuhlisch, Constanze; Pohnert, Georg

    2015-07-01

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

  19. Potential of human saliva for nuclear magnetic resonance-based metabolomics and for health-related biomarker identification

    DEFF Research Database (Denmark)

    Bertram, Hanne Christine; Eggers, Nina; Eller, Nanna

    2009-01-01

    in intensities of several metabolites including trimethylamine oxide (TMAO), choline, propionate, alanine, methanol, and N-acetyl groups. No effects of gender and body mass index (BMI) on the salivary metabolite profile were detected. The relationships between the salivary metabolome and glycated hemoglobin......In the present study, the ability of (1)H nuclear magnetic resonance (NMR) for metabolic profiling of human saliva samples was investigated. High-resolution (1)H NMR spectra were obtained, and signals were assigned to various metabolites mainly representing small organic acids and amino acids....... In addition, the use of human saliva for metabolomic studies was evaluated, and multivariate data analysis revealed that the 92 morning and night samples from 46 subjects could be discriminated with a predictability of 85%. The diurnal effect on the salivary metabolite profile were ascribed to changes...

  20. 1HNMR-Based metabolomic profiling method to develop plasma biomarkers for sensitivity to chronic heat stress in growing pigs.

    Science.gov (United States)

    Dou, Samir; Villa-Vialaneix, Nathalie; Liaubet, Laurence; Billon, Yvon; Giorgi, Mario; Gilbert, Hélène; Gourdine, Jean-Luc; Riquet, Juliette; Renaudeau, David

    2017-01-01

    The negative impact of heat stress (HS) on the production performances in pig faming is of particular concern. Novel diagnostic methods are needed to predict the robustness of pigs to HS. Our study aimed to assess the reliability of blood metabolome to predict the sensitivity to chronic HS of 10 F1 (Large White × Creole) sire families (SF) reared in temperate (TEMP) and in tropical (TROP) regions (n = 56±5 offsprings/region/SF). Live body weight (BW) and rectal temperature (RT) were recorded at 23 weeks of age. Average daily feed intake (AFDI) and average daily gain were calculated from weeks 11 to 23 of age, together with feed conversion ratio. Plasma blood metabolome profiles were obtained by Nuclear Magnetic Resonance spectroscopy (1HNMR) from blood samples collected at week 23 in TEMP. The sensitivity to hot climatic conditions of each SF was estimated by computing a composite index of sensitivity (Isens) derived from a linear combination of t statistics applied to familial BW, ADFI and RT in TEMP and TROP climates. A model of prediction of sensitivity was established with sparse Partial Least Square Discriminant Analysis (sPLS-DA) between the two most robust SF (n = 102) and the two most sensitive ones (n = 121) using individual metabolomic profiles measured in TEMP. The sPLS-DA selected 29 buckets that enabled 78% of prediction accuracy by cross-validation. On the basis of this training, we predicted the proportion of sensitive pigs within the 6 remaining families (n = 337). This proportion was defined as the predicted membership of families to the sensitive category. The positive correlation between this proportion and Isens (r = 0.97, P < 0.01) suggests that plasma metabolome can be used to predict the sensitivity of pigs to hot climate.

  1. 1HNMR-Based metabolomic profiling method to develop plasma biomarkers for sensitivity to chronic heat stress in growing pigs.

    Directory of Open Access Journals (Sweden)

    Samir Dou

    Full Text Available The negative impact of heat stress (HS on the production performances in pig faming is of particular concern. Novel diagnostic methods are needed to predict the robustness of pigs to HS. Our study aimed to assess the reliability of blood metabolome to predict the sensitivity to chronic HS of 10 F1 (Large White × Creole sire families (SF reared in temperate (TEMP and in tropical (TROP regions (n = 56±5 offsprings/region/SF. Live body weight (BW and rectal temperature (RT were recorded at 23 weeks of age. Average daily feed intake (AFDI and average daily gain were calculated from weeks 11 to 23 of age, together with feed conversion ratio. Plasma blood metabolome profiles were obtained by Nuclear Magnetic Resonance spectroscopy (1HNMR from blood samples collected at week 23 in TEMP. The sensitivity to hot climatic conditions of each SF was estimated by computing a composite index of sensitivity (Isens derived from a linear combination of t statistics applied to familial BW, ADFI and RT in TEMP and TROP climates. A model of prediction of sensitivity was established with sparse Partial Least Square Discriminant Analysis (sPLS-DA between the two most robust SF (n = 102 and the two most sensitive ones (n = 121 using individual metabolomic profiles measured in TEMP. The sPLS-DA selected 29 buckets that enabled 78% of prediction accuracy by cross-validation. On the basis of this training, we predicted the proportion of sensitive pigs within the 6 remaining families (n = 337. This proportion was defined as the predicted membership of families to the sensitive category. The positive correlation between this proportion and Isens (r = 0.97, P < 0.01 suggests that plasma metabolome can be used to predict the sensitivity of pigs to hot climate.

  2. Metabolomic and inflammatory mediator based biomarker profiling as a potential novel method to aid pediatric appendicitis identification.

    Science.gov (United States)

    Shommu, Nusrat S; Jenne, Craig N; Blackwood, Jaime; Joffe, Ari R; Martin, Dori-Ann; Thompson, Graham C; Vogel, Hans J

    2018-01-01

    Various limitations hinder the timely and accurate diagnosis of appendicitis in pediatric patients. The present study aims to investigate the potential of metabolomics and cytokine profiling for improving the diagnosis of pediatric appendicitis. Serum and plasma samples were collected from pediatric patients for metabolic and inflammatory mediator analyses respectively. Targeted metabolic profiling was performed using Proton Nuclear Magnetic Resonance Spectroscopy and Flow Injection Analysis Mass Spectrometry/Mass Spectrometry and targeted cytokine/chemokine profiling was completed using a multiplex platform to compare children with and without appendicitis. Twenty-three children with appendicitis and 35 control children without appendicitis from the Alberta Sepsis Network pediatric cohorts were included. Metabolomic profiling revealed clear separation between the two groups with very good sensitivity (80%), specificity (97%), and AUROC (0.93 ± 0.05) values. Inflammatory mediator analysis also distinguished the two groups with high sensitivity (82%), specificity (100%), and AUROC (0.97 ± 0.02) values. A biopattern comprised of 9 metabolites and 7 inflammatory compounds was detected to be significant for the separation between appendicitis and control groups. Integration of these 16 significant compounds resulted in a combined metabolic and cytokine profile that also demonstrated strong separation between the two groups with 81% sensitivity, 100% specificity and AUROC value of 0.96 ± 0.03. The study demonstrated that metabolomics and cytokine mediator profiling is capable of distinguishing children with appendicitis from those without. These results suggest a potential new approach for improving the identification of appendicitis in children.

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

    Science.gov (United States)

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

    2016-07-13

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

  4. Discriminative Analysis of Different Grades of Gaharu (Aquilaria malaccensis Lamk. via 1H-NMR-Based Metabolomics Using PLS-DA and Random Forests Classification Models

    Directory of Open Access Journals (Sweden)

    Siti Nazirah Ismail

    2017-09-01

    Full Text Available Gaharu (agarwood, Aquilaria malaccensis Lamk. is a valuable tropical rainforest product traded internationally for its distinctive fragrance. It is not only popular as incense and in perfumery, but also favored in traditional medicine due to its sedative, carminative, cardioprotective and analgesic effects. The current study addresses the chemical differences and similarities between gaharu samples of different grades, obtained commercially, using 1H-NMR-based metabolomics. Two classification models: partial least squares-discriminant analysis (PLS-DA and Random Forests were developed to classify the gaharu samples on the basis of their chemical constituents. The gaharu samples could be reclassified into a ‘high grade’ group (samples A, B and D, characterized by high contents of kusunol, jinkohol, and 10-epi-γ-eudesmol; an ‘intermediate grade’ group (samples C, F and G, dominated by fatty acid and vanillic acid; and a ‘low grade’ group (sample E and H, which had higher contents of aquilarone derivatives and phenylethyl chromones. The results showed that 1H- NMR-based metabolomics can be a potential method to grade the quality of gaharu samples on the basis of their chemical constituents.

  5. Metabolomics data normalization with EigenMS.

    Directory of Open Access Journals (Sweden)

    Yuliya V Karpievitch

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

  6. Metabolomic studies in pulmonology

    Directory of Open Access Journals (Sweden)

    R. R. Furina

    2015-01-01

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

  7. The food metabolome

    DEFF Research Database (Denmark)

    Scalbert, Augustin; Brennan, Lorraine; Manach, Claudine

    2014-01-01

    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...... 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...

  8. Metabolomic analysis of Echinacea spp. by 1H nuclear magnetic resonance spectrometry and multivariate data analysis technique.

    Science.gov (United States)

    Frédérich, Michel; Jansen, Céline; de Tullio, Pascal; Tits, Monique; Demoulin, Vincent; Angenot, Luc

    2010-01-01

    The genus Echinacea (Asteraceae) comprises about 10 species originally distributed in North America. Three species are very well known as they are used worldwide as medicinal plants: Echinacea purpurea, E. pallida, E. angustifolia. To discriminate between these three Echinacea species and E. simulata by (1)H NMR-based metabolomics. (1)H NMR and multivariate analysis techniques were applied to diverse Echinacea plants including roots and aerial parts, authentic plants, commercial plants and commercial dry extracts. Using the (1)H NMR metabolomics, it was possible, without previous evaporation or separation steps, to obtain a metabolic fingerprint to distinguish between species. A clear distinction between the three pharmaceutical species was possible and some useful metabolites were identified. (c) 2009 John Wiley & Sons, Ltd.

  9. Discovery and identification of potential biomarkers for alcohol-induced oxidative stress based on cellular metabolomics.

    Science.gov (United States)

    Hu, Qingping; Wei, Jianteng; Liu, Yewei; Fei, Xiulan; Hao, Yuwei; Pei, Dong; Di, Duolong

    2017-07-01

    Biomarkers involved in alcohol-induced oxidative stress play an important role in alcoholic liver disease prevention and diagnosis. Alcohol-induced oxidative stress in human liver L-02 cells was used to discover the potential biomarkers. Metabolites from L-02 cells induced by alcohol were measured by high-performance liquid chromatography and mass spectrometry. Fourteen metabolites that allowed discrimination between control and model groups were discovered by multivariate statistical data analysis (i.e. principal components analysis, orthogonal partial least-squares discriminate analysis). Based on the retention time, UV spectrum and LC-MS findings of the samples and compared with the authentic standards, eight biomarkers involved in alcohol-induced oxidative stress, namely, malic acid, oxidized glutathione, γ-glutamyl-cysteinyl-glycine, adenosine triphosphate, phenylalanine, adenosine monophosphate, nitrotyrosine and tryptophan, were identified. These biomarkers offered important targets for disease diagnosis and other researches. Copyright © 2016 John Wiley & Sons, Ltd.

  10. A Machine-Learned Predictor of Colonic Polyps Based on Urinary Metabolomics

    Directory of Open Access Journals (Sweden)

    Roman Eisner

    2013-01-01

    Full Text Available We report an automated diagnostic test that uses the NMR spectrum of a single spot urine sample to accurately distinguish patients who require a colonoscopy from those who do not. Moreover, our approach can be adjusted to tradeoff between sensitivity and specificity. We developed our system using a group of 988 patients (633 normal and 355 who required colonoscopy who were all at average or above-average risk for developing colorectal cancer. We obtained a metabolic profile of each subject, based on the urine samples collected from these subjects, analyzed via 1H-NMR and quantified using targeted profiling. Each subject then underwent a colonoscopy, the gold standard to determine whether he/she actually had an adenomatous polyp, a precursor to colorectal cancer. The metabolic profiles, colonoscopy outcomes, and medical histories were then analysed using machine learning to create a classifier that could predict whether a future patient requires a colonoscopy. Our empirical studies show that this classifier has a sensitivity of 64% and a specificity of 65% and, unlike the current fecal tests, allows the administrators of the test to adjust the tradeoff between the two.

  11. A machine-learned predictor of colonic polyps based on urinary metabolomics.

    Science.gov (United States)

    Eisner, Roman; Greiner, Russell; Tso, Victor; Wang, Haili; Fedorak, Richard N

    2013-01-01

    We report an automated diagnostic test that uses the NMR spectrum of a single spot urine sample to accurately distinguish patients who require a colonoscopy from those who do not. Moreover, our approach can be adjusted to tradeoff between sensitivity and specificity. We developed our system using a group of 988 patients (633 normal and 355 who required colonoscopy) who were all at average or above-average risk for developing colorectal cancer. We obtained a metabolic profile of each subject, based on the urine samples collected from these subjects, analyzed via (1)H-NMR and quantified using targeted profiling. Each subject then underwent a colonoscopy, the gold standard to determine whether he/she actually had an adenomatous polyp, a precursor to colorectal cancer. The metabolic profiles, colonoscopy outcomes, and medical histories were then analysed using machine learning to create a classifier that could predict whether a future patient requires a colonoscopy. Our empirical studies show that this classifier has a sensitivity of 64% and a specificity of 65% and, unlike the current fecal tests, allows the administrators of the test to adjust the tradeoff between the two.

  12. Biomarker identification and pathway analysis of preeclampsia based on serum metabolomics.

    Science.gov (United States)

    Chen, Tingting; He, Ping; Tan, Yong; Xu, Dongying

    2017-03-25

    Preeclampsia presents serious risk of both maternal and fetal morbidity and mortality. Biomarkers for the detection of preeclampsia are critical for risk assessment and targeted intervention. The goal of this study is to screen potential biomarkers for the diagnosis of preeclampsia and to illuminate the pathogenesis of preeclampsia development based on the differential expression network. Two groups of subjects, including healthy pregnant women, subjects with preeclampsia, were recruited for this study. The metabolic profiles of all of the subjects' serum were obtained by liquid chromatography quadruple time-of-flight mass spectrometry. Correlation between metabolites was analyzed by bioinformatics technique. Results showed that the PC(14:0/00), proline betaine and proline were potential sensitive and specific biomarkers for preeclampsia diagnosis and prognosis. Perturbation of corresponding biological pathways, such as iNOS signaling, nitric oxide signaling in the cardiovascular system, mitochondrial dysfunction were responsible for the pathogenesis of preeclampsia. This study indicated that the metabolic profiling had a good clinical significance in the diagnosis of preeclampsia as well as in the study of its pathogenesis. Copyright © 2017 Elsevier Inc. All rights reserved.

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

    Science.gov (United States)

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

    2015-01-01

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

  14. Improving the quality of biomarker candidates in untargeted metabolomics via peak table-based alignment of comprehensive two-dimensional gas chromatography-mass spectrometry data.

    Science.gov (United States)

    Bean, Heather D; Hill, Jane E; Dimandja, Jean-Marie D

    2015-05-15

    The potential of high-resolution analytical technologies like GC×GC/TOF MS in untargeted metabolomics and biomarker discovery has been limited by the development of fully automated software that can efficiently align and extract information from multiple chromatographic data sets. In this work we report the first investigation on a peak-by-peak basis of the chromatographic factors that impact GC×GC data alignment. A representative set of 16 compounds of different chromatographic characteristics were followed through the alignment of 63 GC×GC chromatograms. We found that varying the mass spectral match parameter had a significant influence on the alignment for poorly-resolved peaks, especially those at the extremes of the detector linear range, and no influence on well-chromatographed peaks. Therefore, optimized chromatography is required for proper GC×GC data alignment. Based on these observations, a workflow is presented for the conservative selection of biomarker candidates from untargeted metabolomics analyses. Copyright © 2015 Elsevier B.V. All rights reserved.

  15. A Metabolomics-Based Strategy for the Mechanism Exploration of Traditional Chinese Medicine: Descurainia sophia Seeds Extract and Fractions as a Case Study

    Directory of Open Access Journals (Sweden)

    Ning Zhou

    2017-01-01

    Full Text Available A UPLC-QTOF-MS based metabolomics research was conducted to explore potential biomarkers which would increase our understanding of the model and to assess the integral efficacy of Descurainia sophia seeds extract (DS-A. Additionally, DS-A was split into five fractions in descending order of polarity, which were utilized to illustrate the mechanism together. The 26 identified biomarkers were mainly related to disturbances in phenylalanine, tyrosine, tryptophan, purine, arginine, and proline metabolism. Furthermore, heat map, hierarchical cluster analysis (HCA, and correlation network diagram of biomarkers perturbed by modeling were all conducted. The results of heat map and HCA suggested that fat oil fraction could reverse the abnormal metabolism in the model to some extent; meanwhile the metabolic inhibitory effect produced by the other four fractions helped to relieve cardiac load and compensate the insufficient energy supplement induced by the existing heart and lung injury in model rats. Briefly, the split fractions interfered with the model from different aspects and ultimately constituted the overall effects of extract. In conclusion, the metabolomics method, combined with split fractions of extract, is a powerful approach for illustrating pathologic changes of Chinese medicine syndrome and action mechanisms of traditional Chinese medicine.

  16. Discovery, screening and evaluation of a plasma biomarker panel for subjects with psychological suboptimal health state using (1)H-NMR-based metabolomics profiles.

    Science.gov (United States)

    Tian, Jun-Sheng; Xia, Xiao-Tao; Wu, Yan-Fei; Zhao, Lei; Xiang, Huan; Du, Guan-Hua; Zhang, Xiang; Qin, Xue-Mei

    2016-09-21

    Individuals in the state of psychological suboptimal health keep increasing, only scales and questionnaires were used to diagnose in clinic under current conditions, and symptoms of high reliability and accuracy are destitute. Therefore, the noninvasive and precise laboratory diagnostic methods are needed. This study aimed to develop an objective method through screen potential biomarkers or a biomarker panel to facilitate the diagnosis in clinic using plasma metabolomics. Profiles were based on H-nuclear magnetic resonance ((1)H-NMR) metabolomics techniques combing with multivariate statistical analysis. Furthermore, methods of correlation analysis with Metaboanalyst 3.0 for selecting a biomarker panel, traditional Chinese medicine (TCM) drug intervention for validating the close relations between the biomarker panel and the state and the receiver operating characteristic curves (ROC curves) analysis for evaluation of clinical diagnosis ability were carried out. 9 endogenous metabolites containing trimethylamine oxide (TMAO), glutamine, N-acetyl-glycoproteins, citrate, tyrosine, phenylalanine, isoleucine, valine and glucose were identified and considered as potential biomarkers. Then a biomarker panel consisting of phenylalanine, glutamine, tyrosine, citrate, N-acetyl-glycoproteins and TMAO was selected, which exhibited the highest area under the curve (AUC = 0.971). This study provided critical insight into the pathological mechanism of psychological suboptimal health and would supply a novel and valuable diagnostic method.

  17. Novel Approach to Classify Plants Based on Metabolite-Content Similarity

    Directory of Open Access Journals (Sweden)

    Kang Liu

    2017-01-01

    Full Text Available Secondary metabolites are bioactive substances with diverse chemical structures. Depending on the ecological environment within which they are living, higher plants use different combinations of secondary metabolites for adaptation (e.g., defense against attacks by herbivores or pathogenic microbes. This suggests that the similarity in metabolite content is applicable to assess phylogenic similarity of higher plants. However, such a chemical taxonomic approach has limitations of incomplete metabolomics data. We propose an approach for successfully classifying 216 plants based on their known incomplete metabolite content. Structurally similar metabolites have been clustered using the network clustering algorithm DPClus. Plants have been represented as binary vectors, implying relations with structurally similar metabolite groups, and classified using Ward’s method of hierarchical clustering. Despite incomplete data, the resulting plant clusters are consistent with the known evolutional relations of plants. This finding reveals the significance of metabolite content as a taxonomic marker. We also discuss the predictive power of metabolite content in exploring nutritional and medicinal properties in plants. As a byproduct of our analysis, we could predict some currently unknown species-metabolite relations.

  18. COnsortium of METabolomics Studies (COMETS)

    Science.gov (United States)

    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.

  19. Metabolomics: towards understanding traditional Chinese medicine.

    Science.gov (United States)

    Zhang, Aihua; Sun, Hui; Wang, Zhigang; Sun, Wenjun; Wang, Ping; Wang, Xijun

    2010-12-01

    Metabolomics represent a global understanding of metabolite complement of integrated living systems and dynamic responses to the changes of both endogenous and exogenous factors and has many potential applications and advantages for the research of complex systems. As a systemic approach, metabolomics adopts a "top-down" strategy to reflect the function of organisms from the end products of the metabolic network and to understand metabolic changes of a complete system caused by interventions in a holistic context. This property agrees with the holistic thinking of Traditional Chinese Medicine (TCM), a complex medical science, suggesting that metabolomics has the potential to impact our understanding of the theory behind the evidence-based Chinese medicine. Consequently, the development of robust metabolomic platforms will greatly facilitate, for example, the understanding of the action mechanisms of TCM formulae and the analysis of Chinese herbal (CHM) and mineral medicine, acupuncture, and Chinese medicine syndromes. This review summarizes some of the applications of metabolomics in special TCM issues with an emphasis on metabolic biomarker discovery. © Georg Thieme Verlag KG Stuttgart · New York.

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

    Science.gov (United States)

    Miller, Marion G

    2007-02-01

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

  1. Tools for the functional interpretation of metabolomic experiments.

    Science.gov (United States)

    Chagoyen, Monica; Pazos, Florencio

    2013-11-01

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

  2. UPLC-QTOF MS-Based Serum Metabolomic Profiling Analysis Reveals the Molecular Perturbations Underlying Uremic Pruritus

    Directory of Open Access Journals (Sweden)

    Qiong Wu

    2018-01-01

    Full Text Available As one of the most troublesome complications in patients with chronic renal disease, the etiology of uremic pruritus remains unknown, and the current therapeutic approaches are limited and unsatisfactory. To identify potential biomarkers for improving diagnosis and treatment and obtain a better understanding of the pathogenesis of uremic pruritus, we compared serum metabolome profiles of severe uremic pruritus (HUP patients with mild uremic pruritus (LUP patients using ultraperformance liquid chromatography-quadruple time-of-flight mass spectrometry (UPLC-QTOF MS. Partial least squares discriminant analysis (PLS-DA showed that the metabolic profiles of HUP patients are distinguishable from those of LUP patients. Combining multivariate with univariate analysis, 22 significantly different metabolites between HUP and LUP patients were identified. Nine of the 22 metabolites in combination were characterized by a maximum area-under-receiver operating characteristic curve (AUC = 0.899 with a sensitivity of 85.1% and a specificity of 83.0% distinguishing HUP and LUP. Our results indicate that serum metabolome profiling might serve as a promising approach for the diagnosis of uremic pruritus and that the identified biomarkers may improve the understanding of pathophysiology of this disorder. Because the 9 metabolites were phospholipids, uremic toxins, and steroids, further studies may reveal their possible role in the pathogenesis of uremic pruritus.

  3. GC-MS Based Plasma Metabolomics for Identification of Candidate Biomarkers for Hepatocellular Carcinoma in Egyptian Cohort.

    Directory of Open Access Journals (Sweden)

    Mohammad R Nezami Ranjbar

    Full Text Available This study evaluates changes in metabolite levels in hepatocellular carcinoma (HCC cases vs. patients with liver cirrhosis by analysis of human blood plasma using gas chromatography coupled with mass spectrometry (GC-MS. Untargeted metabolomic analysis of plasma samples from participants recruited in Egypt was performed using two GC-MS platforms: a GC coupled to single quadruple mass spectrometer (GC-qMS and a GC coupled to a time-of-flight mass spectrometer (GC-TOFMS. Analytes that showed statistically significant changes in ion intensities were selected using ANOVA models. These analytes and other candidates selected from related studies were further evaluated by targeted analysis in plasma samples from the same participants as in the untargeted metabolomic analysis. The targeted analysis was performed using the GC-qMS in selected ion monitoring (SIM mode. The method confirmed significant changes in the levels of glutamic acid, citric acid, lactic acid, valine, isoleucine, leucine, alpha tocopherol, cholesterol, and sorbose in HCC cases vs. patients with liver cirrhosis. Specifically, our findings indicate up-regulation of metabolites involved in branched-chain amino acid (BCAA metabolism. Although BCAAs are increasingly used as a treatment for cancer cachexia, others have shown that BCAA supplementation caused significant enhancement of tumor growth via activation of mTOR/AKT pathway, which is consistent with our results that BCAAs are up-regulated in HCC.

  4. Biogeography shaped the metabolome of the genus Espeletia: a phytochemical perspective on an Andean adaptive radiation.

    Science.gov (United States)

    Padilla-González, Guillermo F; Diazgranados, Mauricio; Da Costa, Fernando B

    2017-08-18

    The páramo ecosystem has the highest rate of diversification across plant lineages on earth, of which the genus Espeletia (Asteraceae) is a prime example. The current distribution and molecular phylogeny of Espeletia suggest the influence of Andean geography and past climatic fluctuations on the diversification of this genus. However, molecular markers have failed to reveal subtle biogeographical trends in Espeletia diversification, and metabolomic evidence for allopatric segregation in plants has never been reported. Here, we present for the first time a metabolomics approach based on liquid chromatography-mass spectrometry for revealing subtle biogeographical trends in Espeletia diversification. We demonstrate that Espeletia lineages can be distinguished by means of different metabolic fingerprints correlated to the country of origin on a global scale and to the páramo massif on a regional scale. Distinctive patterns in the accumulation of secondary metabolites according to the main diversification centers of Espeletia are also identified and a comprehensive phytochemical characterization is reported. These findings demonstrate that a variation in the metabolic fingerprints of Espeletia lineages followed the biogeography of this genus, suggesting that our untargeted metabolomics approach can be potentially used as a model to understand the biogeographic history of additional plant groups in the páramo ecosystem.

  5. Metabolomic heterogeneity of pulmonary arterial hypertension.

    Directory of Open Access Journals (Sweden)

    Yidan Zhao

    Full Text Available Although multiple gene and protein expression have been extensively profiled in human pulmonary arterial hypertension (PAH, the mechanism for the development and progression of pulmonary hypertension remains elusive. Analysis of the global metabolomic heterogeneity within the pulmonary vascular system leads to a better understanding of disease progression. Using a combination of high-throughput liquid-and-gas-chromatography-based mass spectrometry, we showed unbiased metabolomic profiles of disrupted glycolysis, increased TCA cycle, and fatty acid metabolites with altered oxidation pathways in the human PAH lung. The results suggest that PAH has specific metabolic pathways contributing to increased ATP synthesis for the vascular remodeling process in severe pulmonary hypertension. These identified metabolites may serve as potential biomarkers for the diagnosis of PAH. By profiling metabolomic alterations of the PAH lung, we reveal new pathogenic mechanisms of PAH, opening an avenue of exploration for therapeutics that target metabolic pathway alterations in the progression of PAH.

  6. Clinical Metabolomics and Glaucoma.

    Science.gov (United States)

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

    2018-01-01

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

  7. Nanoparticle-Assisted Metabolomics

    Directory of Open Access Journals (Sweden)

    Bo Zhang

    2018-03-01

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

  8. Comparison of earthworm responses to petroleum hydrocarbon exposure in aged field contaminated soil using traditional ecotoxicity endpoints and 1H NMR-based metabolomics

    International Nuclear Information System (INIS)

    Whitfield Åslund, Melissa; Stephenson, Gladys L.; Simpson, André J.; Simpson, Myrna J.

    2013-01-01

    1 H NMR metabolomics and conventional ecotoxicity endpoints were used to examine the response of earthworms exposed to petroleum hydrocarbons (PHCs) in soil samples collected from a site that was contaminated with crude oil from a pipeline failure in the mid-1990s. The conventional ecotoxicity tests showed that the soils were not acutely toxic to earthworms (average survival ≥90%), but some soil samples impaired reproduction endpoints by >50% compared to the field control soil. Additionally, metabolomics revealed significant relationships between earthworm metabolic profiles (collected after 2 or 14 days of exposure) and soil properties including soil PHC concentration. Further comparisons by partial least squares regression revealed a significant relationship between the earthworm metabolomic data (collected after only 2 or 14 days) and the reproduction endpoints (measured after 63 days). Therefore, metabolomic responses measured after short exposure periods may be predictive of chronic, ecologically relevant toxicity endpoints for earthworms exposed to soil contaminants. -- Highlights: •Earthworm response to petroleum hydrocarbon exposure in soil is examined. •Metabolomics shows significant changes to metabolic profile after 2 days. •Significant relationships observed between metabolomic and reproduction endpoints. •Metabolomics may have value as a rapid screening tool for chronic toxicity. -- Earthworm metabolomic responses measured after 2 and 14 days are compared to traditional earthworm ecotoxicity endpoints (survival and reproduction) in petroleum hydrocarbon contaminated soil

  9. Plant-based remediation processes

    Energy Technology Data Exchange (ETDEWEB)

    Gupta, Dharmendra Kumar (ed.) [Belgian Nuclear Research Centre (SCK.CEN), Mol (Belgium). Radiological Impact and Performance Assessment Division

    2013-11-01

    A valuable source of information for scientists in the field of environmental pollution and remediation. Describes the latest biotechnological methods for the treatment of contaminated soils. Includes case studies and protocols. Phytoremediation is an emerging technology that employs higher plants for the clean-up of contaminated environments. Basic and applied research have unequivocally demonstrated that selected plant species possess the genetic potential to accumulate, degrade, metabolize and immobilize a wide range of contaminants. The main focus of this volume is on the recent advances of technologies using green plants for remediation of various metals and metalloids. Topics include biomonitoring of heavy metal pollution, amendments of higher uptake of toxic metals, transport of heavy metals in plants, and toxicity mechanisms. Further chapters discuss agro-technological methods for minimizing pollution while improving soil quality, transgenic approaches to heavy metal remediation and present protocols for metal remediation via in vitro root cultures.

  10. Bio-effectors from waste materials as growth promoters, an agronomic and metabolomic study

    Science.gov (United States)

    Alwanney, Deaa; Chami, Ziad Al; Angelica De Pascali, Sandra; Cavoski, Ivana; Fanizzi, Francesco Paolo

    2014-05-01

    Nowadays, improving plant performance by providing growth promoters is a main concern of the organic agriculture. As a consequence of increased food demands, more efficient and alternatives of the current plant nutrition strategies are becoming urgent. Recently, a novel concept "bio-effectors" raised on to describe a group of products that are able to improve plant performance and do not belong to fertilizers or pesticides. Agro-Food processing residues are promising materials as bio-effector. Three plant-derived materials: brewers' spent grain (BSG), fennel processing residues (FPR) and lemon processing residues (LPR) were chosen as bio-effector candidates. Plant-derived materials were characterized in term of total macro and micronutrients content. Green extraction methodology and solvent choice (aqueous; ethanol; and aqueous: ethanol mixture 1:1) was based on the extraction yield as main factor. Optimum extracts, to be used on the tomato test plant, were determined using phytotoxicity test (seed germination test) as main constraint. Thereafter, selected extracts were characterized and secondary metabolites profiling were detected by NMR technique. Selected extracts were applied on tomato in a growth chamber at different doses in comparison to humic-like substances as positive control (Ctrl+) and to a Hoagland solution as negative control (Ctrl-). At the end of the experiment, agronomical parameters were determined and NMR-metabolomic profiling were conducted on tomato seedlings. Results are summarized as follow: (i) raw showed an interesting content, either at nutritional or biological level; (ii) aqueous extraction resulted higher yield than other used solvent; (iii) at high extraction ratio (1:25 for BSG; 1:100 for FPR; and 1:200 for LPR) aqueous extracts were not phytotoxic on the tomato test plant; (iv) all aqueous extract are differently rich in nutrients, aminoacids, sugars and low molecular weight molecules; (v) all extract exhibited a growth promotion at

  11. UHPLC/Q-TOFMS-based metabolomics for the characterization of cold and hot properties of Chinese materia medica.

    Science.gov (United States)

    Wang, Yang; Zhou, Shujun; Wang, Meng; Liu, Shuying; Hu, Yuanjia; He, Chengwei; Li, Peng; Wan, Jian-Bo

    2016-02-17

    The cold/hot property of Chinese materia medica (CMM) and the application of its corresponding knowledge in the diagnosis, differentiation and treatment of diseases have been considered to be the extremely important part of traditional Chinese medicine (TCM). As highly abstracted TCM theory, the cold/hot property of CMMs is still not fully understood and remains to be elucidated by systems biology approach. The cold and hot properties of CMM are mainly defined by the response of the body to a given CMM. Metabolomics is a promising systems biology method to profile entire endogenous metabolites and monitor their fluctuations related to an exogenous stimulus. Thus, a metabolomics approach was applied to characterize the cold and hot properties of CMMs. Mice were intragastrically administered three selected cold property CMMs (i.e., Rheum palmatum L., radix et rhizoma; Coptis chinensis Franch, rhizome and Scutellaria baicalensis Georgi, radix) and three hot property CMMs (i.e., Cinnamomum cassia (L.) J. Presl, cortex; Zingiber officinale Roscoe, rhizoma and Evodia rutaecarpa (Juss.) Benth., fructus) once daily for one week. The comprehensive metabolome changes in the plasma of mice after treatment with cold or hot property CMMs were characterized by ultra-high performance liquid chromatography/time of flight mass spectrometry (UHPLC/Q-TOF-MS), and the potential biomarkers related to cold and hot properties of CMM were explored. Metabolites perturbation in plasma occurs after treatment with cold CMMs and hot CMMs in mice, and 15 and 16 differential biomarkers were identified to be associated with the cold and hot properties of CMMs, respectively. Among them, LPC (18:0), LPC (18:1), LPC (20:4) and LPC (20:5) showed decreased trends in the cold property CMM treated groups, but increased in the hot property CMM treated groups. There is a strong connection between the cold/hot property of CMMs and lysophosphatidylcholines metabolism. This study offers new insight

  12. Metabolomics for functional genomics, systems biology, and biotechnology.

    Science.gov (United States)

    Saito, Kazuki; Matsuda, Fumio

    2010-01-01

    Metabolomics now plays a significant role in fundamental plant biology and applied biotechnology. Plants collectively produce a huge array of chemicals, far more than are produced by most other organisms; hence, metabolomics is of great importance in plant biology. Although substantial improvements have been made in the field of metabolomics, the uniform annotation of metabolite signals in databases and informatics through international standardization efforts remains a challenge, as does the development of new fields such as fluxome analysis and single cell analysis. The principle of transcript and metabolite cooccurrence, particularly transcriptome coexpression network analysis, is a powerful tool for decoding the function of genes in Arabidopsis thaliana. This strategy can now be used for the identification of genes involved in specific pathways in crops and medicinal plants. Metabolomics has gained importance in biotechnology applications, as exemplified by quantitative loci analysis, prediction of food quality, and evaluation of genetically modified crops. Systems biology driven by metabolome data will aid in deciphering the secrets of plant cell systems and their application to biotechnology.

  13. Metabolomics-based evidence of the hypoglycemic effect of Ge-Gen-Jiao-Tai-Wan in type 2 diabetic rats via UHPLC-QTOF/MS analysis.

    Science.gov (United States)

    Wang, Wenbo; Zhao, Linlin; He, Zhenyu; Wu, Ning; Li, Qiuxia; Qiu, Xinjian; Zhou, Lu; Wang, Dongsheng

    2018-03-23

    Ge-Gen-Jiao-Tai-Wan (GGJTW) formula, derived from traditional Chinese herbal medicine, is composed of Pueraria montana var. lobata (Willd.) Sanjappa & Pradeep (Ge-Gen in Chinese), Coptis chinensis Franch (Huang-Lian), and Cinnamomum cassia (L.) J. Presl (Rou-Gui). GGJTW is used for treatment of diabetes in China, reflecting the potent hypoglycemic effect of its ingredients. However, little is known of the hypoglycemic effect of GGJTW and the underlying metabolic mechanism. This study aimed to investigate the hypoglycemic effect of GGJTW in type 2 diabetic rats and the metabolic mechanism of action. Ultra high-performance liquid chromatography coupled with quadrupole-time-of-flight tandem mass spectrometry (UHPLC-QTOF/MS)-based metabolomics approach was used for monitoring hyperglycaemia induced by high-sugar high-fat fodder and streptozotocin (STZ), and the protective effect of GGJTW. Dynamic fasting blood glucose (FBG) levels, body weight, and biochemical parameters, including lipid levels, hepatic-renal function, and hepatic histopathology were used to confirm the hyperglycaemic toxicity and attenuation effects. An orthogonal partial least squared-discriminant analysis (OPLS-DA) approach highlighted significant differences in the metabolome of the healthy control, diabetic, and drug-treated rats. The metabolomics pathway analysis (MetPA) and Kyoto encyclopedia of genes and genomes (KEGG) database were used to investigate the underlying metabolic pathways. Metabolic profiling revealed 37 metabolites as the most potential biomarker metabolites distinguishing GGJTW-treated rats from model rats. Most of the metabolites were primarily associated with bile acid metabolism and lipid metabolism. The most critical pathway was primary bile acid biosynthesis pathway involving the up-regulation of the levels of cholic acid (CA), chenodeoxycholic acid (CDCA), taurocholic acid (TCA), glycocholic acid (GCA), taurochenodesoxycholic acid (TCDCA), and taurine. The significantly

  14. Method validation for preparing serum and plasma samples from human blood for downstream proteomic, metabolomic, and circulating nucleic acid-based applications.

    Science.gov (United States)

    Ammerlaan, Wim; Trezzi, Jean-Pierre; Lescuyer, Pierre; Mathay, Conny; Hiller, Karsten; Betsou, Fay

    2014-08-01

    Formal method validation for biospecimen processing in the context of accreditation in laboratories and biobanks is lacking. Serum and plasma processing protocols were validated for fitness-for-purpose in terms of key downstream endpoints, and this article demonstrates methodology for biospecimen processing method validation. Serum and plasma preparation from human blood was optimized for centrifugation conditions with respect to microparticle counts. Optimal protocols were validated for methodology and reproducibility in terms of acceptance criteria based on microparticle counts, DNA and hemoglobin concentration, and metabolomic and proteomic profiles. These parameters were also used to evaluate robustness for centrifugation temperature (4°C versus room temperature [RT]), deceleration (low, medium, high) and blood stability (after a 2-hour delay). Optimal protocols were 10-min centrifugation for serum and 20-min for plasma at 2000 g, medium brake, RT. Methodology and reproducibility acceptance criteria were met for both protocols except for reproducibility of plasma metabolomics. Overall, neither protocol was robust for centrifugation at 4°C versus RT. RT gave higher microparticles and free DNA yields in serum, and fewer microparticles with less hemolysis in plasma. Overall, both protocols were robust for fast, medium, and low deceleration, with a medium brake considered optimal. Pre-centrifugation stability after a 2-hour delay was seen at both temperatures for hemoglobin concentration and proteomics, but not for microparticle counts. We validated serum and plasma collection methods suitable for downstream protein, metabolite, or free nucleic acid-based applications. Temperature and pre-centrifugation delay can influence analytic results, and laboratories and biobanks should systematically record these conditions in the scope of accreditation.

  15. Investigating correlations in the altered metabolic profiles of obese and diabetic subjects in a South Indian Asian population using an NMR-based metabolomic approach.

    Science.gov (United States)

    Gogna, Navdeep; Krishna, Murahari; Oommen, Anup Mammen; Dorai, Kavita

    2015-02-01

    It is well known that obesity/high body mass index (BMI) plays a key role in the evolution of insulin resistance and type-2 diabetes mellitus (T2DM). However, the exact mechanism underlying its contribution is still not fully understood. This work focuses on an NMR-based metabolomic investigation of the serum profiles of diabetic, obese South Indian Asian subjects. (1)H 1D and 2D NMR experiments were performed to profile the altered metabolic patterns of obese diabetic subjects and multivariate statistical methods were used to identify metabolites that contributed significantly to the differences in the samples of four different subject groups: diabetic and non-diabetic with low and high BMIs. Our analysis revealed that the T2DM-high BMI group has higher concentrations of saturated fatty acids, certain amino acids (leucine, isoleucine, lysine, proline, threonine, valine, glutamine, phenylalanine, histidine), lactic acid, 3-hydroxybutyric acid, choline, 3,7-dimethyluric acid, pantothenic acid, myoinositol, sorbitol, glycerol, and glucose, as compared to the non-diabetic-low BMI (control) group. Of these 19 identified significant metabolites, the levels of saturated fatty acids, lactate, valine, isoleucine, and phenylalanine are also higher in obese non-diabetic subjects as compared to control subjects, implying that this set of metabolites could be identified as potential biomarkers for the onset of diabetes in subjects with a high BMI. Our work validates the utility of NMR-based metabolomics in conjunction with multivariate statistical analysis to provide insights into the underlying metabolic pathways that are perturbed in diabetic subjects with a high BMI.

  16. From models to crop species: caveats and solutions for translational metabolomics

    Directory of Open Access Journals (Sweden)

    Takayuki eTohge

    2011-10-01

    Full Text Available Although plant metabolomics is largely carried out on Arabidopsis it is essentially genome-independent, and thus potentially applicable to a wide range of species. However, transfer of between species, or even between different tissues of the same species, is not facile. This is because the reliability of protocols for harvesting, handling and analysis depends on the biological features and chemical composition of the plant tissue. In parallel with the diversification of model species it is important to establish good handling and analytic practice, in order to augment computational comparisons between tissues and species. LC-MS-based metabolomics is one of the powerful approaches for metabolite profiling. By using a combination of different extraction methods, separation columns and ion detection, a very wide range of metabolites can be analysed. However, its application requires careful attention to exclude potential pitfalls, including artifactual changes in metabolite levels during sample preparation and analytic errors due to ion-suppression. Here we provide case studies with two different LC-MS-based metabolomics platforms and four species (Arabidopsis thaliana, Chlamydomonas reinhardtii, Solanum lycopersicum and Oryza sativa that illustrate how such dangers can be detected and circumvented.

  17. {sup 1}H-NMR-based metabolomics studies of the toxicity of mesoporous carbon nanoparticles in Zebrafish (Daniorerio)

    Energy Technology Data Exchange (ETDEWEB)

    Raja, Ganesan; Kim, Si Won; Yoon, Da Hye; Yoon, Chang Shin; Kim, Suhkmann [Dept. of Chemistry, Center for Proteome Biophysics and Chemistry Institute for Functional Materials, Pusan National University, Busan (Korea, Republic of)

    2017-02-15

    Mesoporous carbon nanoparticles (MCNs) have been applied in a variety of drug/gene carriers. In addition to their potential benefits, many studies of their potential toxicity have been reported, showing the limitations of metabolic contextualization. In this study, we conducted {sup 1}H-nuclear magnetic resonance (NMR) profiling combined with statistical methods such as orthogonal partial least squares discriminant analysis and Pearson correlation analysis to assess metabolic alterations in the whole body of zebrafish (Danio rerio) in the presence of various concentrations of MCNs. The MCN exposure influenced numerous metabolites in energy metabolism (e.g., metabolites involved in glycolysis and tricarboxylic acid cycle) and disturbed the balance of neurotransmitters and osmoregulators. Our findings demonstrate the potential applicability of using a metabolomics approach to determine underlying metabolic disturbances caused by MCNs.

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

    Science.gov (United States)

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

    2015-08-01

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

  19. Linking metabolomics data to underlying metabolic regulation

    Directory of Open Access Journals (Sweden)

    Thomas eNägele

    2014-11-01

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

  20. Metallomics and NMR-based metabolomics of Chlorella sp. reveal the synergistic role of copper and cadmium in multi-metal toxicity and oxidative stress.

    Science.gov (United States)

    Zhang, Wenlin; Tan, Nicole G J; Fu, Baohui; Li, Sam F Y

    2015-03-01

    Industrial wastewaters often contain high levels of metal mixtures, in which metal mixtures may have synergistic or antagonistic effects on aquatic organisms. A combination of metallomics and nuclear magnetic resonance spectroscopy (NMR)-based metabolomics was employed to understand the consequences of multi-metal systems (Cu, Cd, Pb) on freshwater microalgae. Morphological characterization, cell viability and chlorophyll a determination of metal-spiked Chlorella sp. suggested synergistic effects of Cu and Cd on growth inhibition and toxicity. While Pb has no apparent effect on Chlorella sp. metabolome, a substantial decrease of sucrose, amino acid content and glycerophospholipid precursors in Cu-spiked microalgae revealed Cu-induced oxidative stress. Addition of Cd to Cu-spiked cultures induced more drastic metabolic perturbations, hence we confirmed that Cu and Cd synergistically influenced photosynthesis inhibition, oxidative stress and membrane degradation. Total elemental analysis revealed a significant decrease in K, and an increase in Na, Mg, Zn and Mn concentrations in Cu-spiked cultures. This indicated that Cu is more toxic to Chlorella sp. as compared to Cd or Pb, and the combination of Cu and Cd has a strong synergistic effect on Chlorella sp. oxidative stress induction. Oxidative stress is confirmed by liquid chromatography tandem mass spectrometry analysis, which demonstrated a drastic decrease in the GSH/GSSG ratio solely in Cu-spiked cultures. Interestingly, we observed Cu-facilitated Cd and Pb bioconcentration in Chlorella sp. The absence of phytochelatins and an increment of extracellular polymeric substances (EPS) yields in Cu-spiked cultures suggested that the mode of bioconcentration of Cd and Pb is through adsorption of free metals onto the algal EPS rather than intracellular chelation to phytochelatins.

  1. Metabolomic changes of Brassica rapa under biotic stress

    NARCIS (Netherlands)

    Abdel-Farid Ali, Ibrahim Bayoumi

    2009-01-01

    It has been shown by this thesis that plant metabolomics is a promising tool for studying the interaction between B. rapa and pathogenic fungi. It gives a picture of the plant metabolites during the interaction. Brassica rapa has many defense related compounds such as glucosinolates, IAA,

  2. Chemometrics Methods and Strategies in Metabolomics.

    Science.gov (United States)

    Pinto, Rui Climaco

    2017-01-01

    Chemometrics has been a fundamental discipline for the development of metabolomics, while symbiotically growing with it. From design of experiments, through data processing, to data analysis, chemometrics tools are used to design, process, visualize, explore and analyse metabolomics data.In this chapter, the most commonly used chemometrics methods for data analysis and interpretation of metabolomics experiments will be presented, with focus on multivariate analysis. These are projection-based linear methods, like principal component analysis (PCA) and orthogonal projection to latent structures (OPLS), which facilitate interpretation of the causes behind the observed sample trends, correlation with outcomes or group discrimination analysis. Validation procedures for multivariate methods will be presented and discussed.Univariate analysis is briefly discussed in the context of correlation-based linear regression methods to find associations to outcomes or in analysis of variance-based and logistic regression methods for class discrimination. These methods rely on frequentist statistics, with the determination of p-values and corresponding multiple correction procedures.Several strategies of design-analysis of metabolomics experiments will be discussed, in order to guide the reader through different setups, adopted to better address some experimental issues and to better test the scientific hypotheses.

  3. Model-based explanation of plant knowledge

    Energy Technology Data Exchange (ETDEWEB)

    Huuskonen, P.J. [VTT Electronics, Oulu (Finland). Embedded Software

    1997-12-31

    This thesis deals with computer explanation of knowledge related to design and operation of industrial plants. The needs for explanation are motivated through case studies and literature reviews. A general framework for analysing plant explanations is presented. Prototypes demonstrate key mechanisms for implementing parts of the framework. Power plants, steel mills, paper factories, and high energy physics control systems are studied to set requirements for explanation. The main problems are seen to be either lack or abundance of information. Design knowledge in particular is found missing at plants. Support systems and automation should be enhanced with ways to explain plant knowledge to the plant staff. A framework is formulated for analysing explanations of plant knowledge. It consists of three parts: 1. a typology of explanation, organised by the class of knowledge (factual, functional, or strategic) and by the target of explanation (processes, automation, or support systems), 2. an identification of explanation tasks generic for the plant domain, and 3. an identification of essential model types for explanation (structural, behavioural, functional, and teleological). The tasks use the models to create the explanations of the given classes. Key mechanisms are discussed to implement the generic explanation tasks. Knowledge representations based on objects and their relations form a vocabulary to model and present plant knowledge. A particular class of models, means-end models, are used to explain plant knowledge. Explanations are generated through searches in the models. Hypertext is adopted to communicate explanations over dialogue based on context. The results are demonstrated in prototypes. The VICE prototype explains the reasoning of an expert system for diagnosis of rotating machines at power plants. The Justifier prototype explains design knowledge obtained from an object-oriented plant design tool. Enhanced access mechanisms into on-line documentation are

  4. Principles for ecologically based invasive plant management

    Science.gov (United States)

    Jeremy J. James; Brenda S. Smith; Edward A. Vasquez; Roger L. Sheley

    2010-01-01

    Land managers have long identified a critical need for a practical and effective framework for designing restoration strategies, especially where invasive plants dominate. A holistic, ecologically based, invasive plant management (EBIPM) framework that integrates ecosystem health assessment, knowledge of ecological processes, and adaptive management into a successional...

  5. NMR-based plasma metabolomic discrimination for male fertility assessment of rats treated with Eurycoma longifolia extracts.

    Science.gov (United States)

    Ebrahimi, Forough; Ibrahim, Baharudin; Teh, Chin-Hoe; Murugaiyah, Vikneswaran; Chan, Kit-Lam

    2017-06-01

    Male infertility is one of the leading causes of infertility which affects many couples worldwide. Semen analysis is a routine examination of male fertility status which is usually performed on semen samples obtained through masturbation that may be inconvenient to patients. Eurycoma longifolia (Tongkat Ali, TA), native to Malaysia, has been traditionally used as a remedy to boost male fertility. In our recent studies in rats, upon the administration of high-quassinoid content extracts of TA including TA water (TAW), quassinoid-rich TA (TAQR) extracts, and a low-quassinoid content extract including quassinoid-poor TA (TAQP) extract, sperm count (SC) increased in TAW- and TAQR-treated rats when compared to the TAQP-treated and control groups. Consequently, the rats were divided into normal- (control and TAQP-treated) and high- (TAW- and TAQR-treated) SC groups [Ebrahimi et al. 2016]. Post-treatment rat plasma was collected. An optimized plasma sample preparation method was developed with respect to the internal standards sodium 3- (trimethylsilyl) propionate- 2,2,3,3- d4 (TSP) and deuterated 4-dimethyl-4-silapentane-1-ammonium trifluoroacetate (DSA). Carr-Purcell-Meibum-Gill (CPMG) experiments combined with orthogonal partial least squares discriminant analysis (OPLS-DA) was employed to evaluate plasma metabolomic changes in normal- and high-SC rats. The potential biomarkers associated with SC increase were investigated to assess fertility by capturing the metabolomic profile of plasma. DSA was selected as the optimized internal standard for plasma analysis due to its significantly smaller half-height line width (W h/2 ) compared to that of TSP. The validated OPLS-DA model clearly discriminated the CPMG profiles in regard to the SC level. Plasma profiles of the high-SC group contained higher levels of alanine, lactate, and histidine, while ethanol concentration was significantly higher in the normal-SC group. This approach might be a new alternative applicable to

  6. UPLC-QTOFMS based metabolomics followed by stepwise partial least square-discriminant analysis (PLS-DA) explore the possible relation between the variations in secondary metabolites and the phylogenetic divergences of the genus Panax.

    Science.gov (United States)

    Nguyen, Huy Truong; Lee, Dong-Kyu; Lee, Won Jun; Lee, GwangJin; Yoon, Sang Jun; Shin, Byong-Kyu; Nguyen, Minh Duc; Park, Jeong Hill; Lee, Jeongmi; Kwon, Sung Won

    2016-02-15

    Phylogenetic and metabolomic approaches have long been employed to study evolutionary relationships among plants. Nonetheless, few studies have examined the difference in metabolites within a clade and between clades of the phylogenetic tree. We attempted to relate phylogenetic studies to metabolomics using stepwise partial least squares-discriminant analysis (PLS-DA) for the genus Panax. Samples were analyzed by ultra-performance liquid chromatography-quadrupole time of flight mass spectrometry (UPLC-QTOFMS) to obtain metabolite profiles. Initially, conventional principal component analysis was subsequently applied to the metabolomic data to show the limitations in relating the expression of metabolites to divisions in the phylogenetic tree. Thereafter, we introduced stepwise PLS-DA with optimized scaling methods, which were properly applied according to the branches of the phylogenetic tree of the four species. Our approach highlighted metabolites of interest by elucidating the directions and degrees of metabolic alterations in each clade of the phylogenetic tree. The results revealed the relationship between metabolic changes in the genus Panax and its species' evolutionary adaptations to different climates. We believe our method will be useful to help understand the metabolite-evolution relationship. Copyright © 2016 Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

    Tebani, Abdellah; Afonso, Carlos; Bekri, Soumeya

    2017-08-24

    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.

  8. UPLC/ESI-QTOF-MS-based metabolomics survey on the toxicity of triptolide and detoxication of licorice.

    Science.gov (United States)

    Wang, Zhuo; Liu, Jian-Qun; Xu, Jin-Di; Zhu, He; Kong, Ming; Zhang, Guo-Hua; Duan, Su-Min; Li, Xiu-Yang; Li, Guang-Fu; Liu, Li-Fang; Li, Song-Lin

    2017-06-01

    Triptolide (TP) from Tripterygium wilfordii has been demonstrated to possess anti-inflammatory, immunosuppressive, and anticancer activities. TP is specially used for the treatment of awkward rheumatoid arthritis, but its clinical application is confined by intense side effects. It is reported that licorice can obviously reduce the toxicity of TP, but the detailed mechanisms involved have not been comprehensively investigated. The current study aimed to explore metabolomics characteristics of the toxic reaction induced by TP and the intervention effect of licorice water extraction (LWE) against such toxicity. Obtained urine samples from control, TP and TP + LWE treated rats were analyzed by UPLC/ESI-QTOF-MS. The metabolic profiles of the control and the TP group were well differentiated by the principal component analysis and orthogonal partial least squares-discriminant analysis. The toxicity of TP was demonstrated to be evolving along with the exposure time of TP. Eight potential biomarkers related to TP toxicity were successfully identified in urine samples. Furthermore, LWE treatment could attenuate the change in six of the eight identified biomarkers. Functional pathway analysis revealed that the alterations in these metabolites were associated with tryptophan, pantothenic acid, and porphyrin metabolism. Therefore, it was concluded that LWE demonstrated interventional effects on TP toxicity through regulation of tryptophan, pantothenic acid, and porphyrin metabolism pathways, which provided novel insights into the possible mechanisms of TP toxicity as well as the potential therapeutic effects of LWE against such toxicity. Copyright © 2017 China Pharmaceutical University. Published by Elsevier B.V. All rights reserved.

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

    Directory of Open Access Journals (Sweden)

    Jie Sun

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

  10. Metabolomic Identification of Subtypes of Nonalcoholic Steatohepatitis.

    Science.gov (United States)

    Alonso, Cristina; Fernández-Ramos, David; Varela-Rey, Marta; Martínez-Arranz, Ibon; Navasa, Nicolás; Van Liempd, Sebastiaan M; Lavín Trueba, José L; Mayo, Rebeca; Ilisso, Concetta P; de Juan, Virginia G; Iruarrizaga-Lejarreta, Marta; delaCruz-Villar, Laura; Mincholé, Itziar; Robinson, Aaron; Crespo, Javier; Martín-Duce, Antonio; Romero-Gómez, Manuel; Sann, Holger; Platon, Julian; Van Eyk, Jennifer; Aspichueta, Patricia; Noureddin, Mazen; Falcón-Pérez, Juan M; Anguita, Juan; Aransay, Ana M; Martínez-Chantar, María Luz; Lu, Shelly C; Mato, José M

    2017-05-01

    Nonalcoholic fatty liver disease (NAFLD) is a consequence of defects in diverse metabolic pathways that involve hepatic accumulation of triglycerides. Features of these aberrations might determine whether NAFLD progresses to nonalcoholic steatohepatitis (NASH). We investigated whether the diverse defects observed in patients with NAFLD are caused by different NAFLD subtypes with specific serum metabolomic profiles, and whether these can distinguish patients with NASH from patients with simple steatosis. We collected liver and serum from methionine adenosyltransferase 1a knockout (MAT1A-KO) mice, which have chronically low levels of hepatic S-adenosylmethionine (SAMe) and spontaneously develop steatohepatitis, as well as C57Bl/6 mice (controls); the metabolomes of all samples were determined. We also analyzed serum metabolomes of 535 patients with biopsy-proven NAFLD (353 with simple steatosis and 182 with NASH) and compared them with serum metabolomes of mice. MAT1A-KO mice were also given SAMe (30 mg/kg/day for 8 weeks); liver samples were collected and analyzed histologically for steatohepatitis. Livers of MAT1A-KO mice were characterized by high levels of triglycerides, diglycerides, fatty acids, ceramides, and oxidized fatty acids, as well as low levels of SAMe and downstream metabolites. There was a correlation between liver and serum metabolomes. We identified a serum metabolomic signature associated with MAT1A-KO mice that also was present in 49% of the patients; based on this signature, we identified 2 NAFLD subtypes. We identified specific panels of markers that could distinguish patients with NASH from patients with simple steatosis for each subtype of NAFLD. Administration of SAMe reduced features of steatohepatitis in MAT1A-KO mice. In an analysis of serum metabolomes of patients with NAFLD and MAT1A-KO mice with steatohepatitis, we identified 2 major subtypes of NAFLD and markers that differentiate steatosis from NASH in each subtype. These might be

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2010-02-19

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

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

    International Nuclear Information System (INIS)

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

    2010-01-01

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

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

    Science.gov (United States)

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

    2017-06-01

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

  14. Impact of dietary polydextrose fiber on the human gut metabolome.

    Science.gov (United States)

    Lamichhane, Santosh; Yde, Christian C; Forssten, Sofia; Ouwehand, Arthur C; Saarinen, Markku; Jensen, Henrik Max; Gibson, Glenn R; Rastall, Robert; Fava, Francesca; Bertram, Hanne Christine

    2014-10-08

    The aim of the present study was to elucidate the impact of polydextrose PDX an soluble fiber, on the human fecal metabolome by high-resolution nuclear magnetic resonance (NMR) spectroscopy-based metabolomics in a dietary intervention study (n = 12). Principal component analysis (PCA) revealed a strong effect of PDX consumption on the fecal metabolome, which could be mainly ascribed to the presence of undigested fiber and oligosaccharides formed from partial degradation of PDX. Our results demonstrate that NMR-based metabolomics is a useful technique for metabolite profiling of feces and for testing compliance to dietary fiber intake in such trials. In addition, novel associations between PDX and the levels of the fecal metabolites acetate and propionate could be identified. The establishment of a correlation between the fecal metabolome and levels of Bifidobacterium (R(2) = 0.66) and Bacteroides (R(2) = 0.46) demonstrates the potential of NMR-based metabolomics to elucidate metabolic activity of bacteria in the gut.

  15. Microbial metabolomics : Toward a platform with full metabolome coverage

    NARCIS (Netherlands)

    Werf, M.J.v.d.; Overkamp, K.M.; Muilwijk, B.; Coulier, L.; Hankemeier, T.

    2007-01-01

    Achieving metabolome data with satisfactory coverage is a formidable challenge in metabolomics because metabolites are a chemically highly diverse group of compounds. Here we present a strategy for the development of an advanced analytical platform that allows the comprehensive analysis of microbial

  16. Non-invasive assessment of culture media from goat cloned embryos associated with subjective morphology by gas chromatography - mass spectroscopy-based metabolomic analysis.

    Science.gov (United States)

    Zhang, Yan-Li; Zhang, Guo-Min; Jia, Ruo-Xin; Wan, Yong-Jie; Yang, Hua; Sun, Ling-Wei; Han, Le; Wang, Feng

    2018-01-01

    Pre-implantation embryo metabolism demonstrates distinctive characteristics associated with the development potential of embryos. We aim to determine if metabolic differences correlate with embryo morphology. In this study, gas chromatography - mass spectroscopy (GC-MS)-based metabolomics was used to assess the culture media of goat cloned embryos collected from high-quality (HQ) and low-quality (LQ) groups based on morphology. Expression levels of amino acid transport genes were further examined by quantitative real-time PCR. Results showed that the HQ group presented higher percentages of blastocysts compared with the LQ counterparts (P culture media of the HQ group showed lower levels of valin, lysine, glutamine, mannose and acetol, and higher levels of glucose, phytosphingosine and phosphate than those of the LQ group. Additionally, expression levels of amino acid transport genes SLC1A5 and SLC3A2 were significantly lower in the HQ group than the LQ group (P culture media. The biochemical profiles may help to select the most in vitro viable embryos. © 2017 Japanese Society of Animal Science.

  17. NMR-Based Metabolomic Investigations on the Differential Responses in Adductor Muscles from Two Pedigrees of Manila Clam Ruditapes philippinarum to Cadmium and Zinc

    Directory of Open Access Journals (Sweden)

    Junbao Yu

    2011-09-01

    Full Text Available Manila clam Ruditapes philippinarum is one of the most important economic species in shellfishery in China due to its wide geographic distribution and high tolerance to environmental changes (e.g., salinity, temperature. In addition, Manila clam is a good biomonitor/bioindicator in “Mussel Watch Programs” and marine environmental toxicology. However, there are several pedigrees of R. philippinarum distributed in the marine environment in China. No attention has been paid to the biological differences between various pedigrees of Manila clams, which may introduce undesirable biological variation in toxicology studies. In this study, we applied NMR-based metabolomics to detect the biological differences in two main pedigrees (White and Zebra of R. philippinarum and their differential responses to heavy metal exposures (Cadmium and Zinc using adductor muscle as a target tissue to define one sensitive pedigree of R. philippinarum as biomonitor for heavy metals. Our results indicated that there were significant metabolic differences in adductor muscle tissues between White and Zebra clams, including higher levels of alanine, glutamine, hypotaurine, phosphocholine and homarine in White clam muscles and higher levels of branched chain amino acids (valine, leucine and isoleucine, succinate and 4-aminobutyrate in Zebra clam muscles, respectively. Differential metabolic responses to heavy metals between White and Zebra clams were also found. Overall, we concluded that White pedigree of clam could be a preferable bioindicator/biomonitor in marine toxicology studies and for marine heavy metals based on the relatively high sensitivity to heavy metals.

  18. Matrix removal in state of the art sample preparation methods for serum by charged aerosol detection and metabolomics-based LC-MS.

    Science.gov (United States)

    Schimek, Denise; Francesconi, Kevin A; Mautner, Anton; Libiseller, Gunnar; Raml, Reingard; Magnes, Christoph

    2016-04-07

    Investigations into sample preparation procedures usually focus on analyte recovery with no information provided about the fate of other components of the sample (matrix). For many analyses, however, and particularly those using liquid chromatography-mass spectrometry (LC-MS), quantitative measurements are greatly influenced by sample matrix. Using the example of the drug amitriptyline and three of its metabolites in serum, we performed a comprehensive investigation of nine commonly used sample clean-up procedures in terms of their suitability for preparing serum samples. We were monitoring the undesired matrix compounds using a combination of charged aerosol detection (CAD), LC-CAD, and a metabolomics-based LC-MS/MS approach. In this way, we compared analyte recovery of protein precipitation-, liquid-liquid-, solid-phase- and hybrid solid-phase extraction methods. Although all methods provided acceptable recoveries, the highest recovery was obtained by protein precipitation with acetonitrile/formic acid (amitriptyline 113%, nortriptyline 92%, 10-hydroxyamitriptyline 89%, and amitriptyline N-oxide 96%). The quantification of matrix removal by LC-CAD showed that the solid phase extraction method (SPE) provided the lowest remaining matrix load (48-123 μg mL(-1)), which is a 10-40 fold better matrix clean-up than the precipitation- or hybrid solid phase extraction methods. The metabolomics profiles of eleven compound classes, comprising 70 matrix compounds showed the trends of compound class removal for each sample preparation strategy. The collective data set of analyte recovery, matrix removal and matrix compound profile was used to assess the effectiveness of each sample preparation method. The best performance in matrix clean-up and practical handling of small sample volumes was showed by the SPE techniques, particularly HLB SPE. CAD proved to be an effective tool for revealing the considerable differences between the sample preparation methods. This detector can

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

    Science.gov (United States)

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

    2012-01-01

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

  20. A Plant-Based Nutrition Program.

    Science.gov (United States)

    Evans, Joanne; Magee, Alexandra; Dickman, Kathy; Sutter, Rebecca; Sutter, Caroline

    2017-03-01

    : Proper nutrition is an important but often overlooked component of preventive care and disease management. Following a plant-based diet in particular has been shown to have dramatic effects on health and well-being in a relatively short period of time. For this reason, nurses at three faculty-led community health clinics participated in a nutrition educational program, following a plant-based diet for 21 days. They sought to improve their knowledge of plant-based nutrition and experience firsthand the benefits of such a diet. The authors conclude that this type of program, with its experiential component and beneficial personal health results, has the potential to influence a larger nursing audience as participants apply their knowledge and experience to patient care and to classroom discussions with nursing students.

  1. Comparative metabolomics in Glycine max and Glycine soja under salt stress to reveal the phenotypes of their offspring.

    Science.gov (United States)

    Lu, Yonghai; Lam, Honming; Pi, Erxu; Zhan, Qinglei; Tsai, Sauna; Wang, Chunmei; Kwan, Yiuwa; Ngai, Saiming

    2013-09-11

    Metabolomics is developing as an important functional genomics tool for understanding plant systems' response to genetic and environmental changes. Here, we characterized the metabolic changes of cultivated soybean C08 (Glycine max L. Merr) and wild soybean W05 (Glycine soja Sieb.et Zucc.) under salt stress using MS-based metabolomics, in order to reveal the phenotypes of their eight hybrid offspring (9H0086, 9H0124, 9H0391, 9H0736, 9H0380, 9H0400, 9H0434, and 9H0590). Total small molecule extracts of soybean seedling leaves were profiled by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-Fourier transform mass spectrometry (LC-FT/MS). We found that wild soybean contained higher amounts of disaccharides, sugar alcohols, and acetylated amino acids than cultivated soybean, but with lower amounts of monosaccharides, carboxylic acids, and unsaturated fatty acids. Further investigations demonstrated that the ability of soybean to tolerate salt was mainly based on synthesis of compatible solutes, induction of reactive oxygen species (ROS) scavengers, cell membrane modifications, and induction of plant hormones. On the basis of metabolic phenotype, the salt-tolerance abilities of 9H0086, 9H0124, 9H0391, 9H0736, 9H0380, 9H0400, 9H0434, and 9H0590 were discriminated. Our results demonstrated that MS-based metabolomics provides a fast and powerful approach to discriminate the salt-tolerance characteristics of soybeans.

  2. Phytochemical Profiles and Antimicrobial Activities of Allium cepa Red cv. and A. sativum Subjected to Different Drying Methods: A Comparative MS-Based Metabolomics

    Directory of Open Access Journals (Sweden)

    Mohamed A. Farag

    2017-05-01

    Full Text Available Plants of the Allium genus produce sulphur compounds that give them a characteristic (alliaceous flavour and mediate for their medicinal use. In this study, the chemical composition and antimicrobial properties of Allium cepa red cv. and A. sativum in the context of three different drying processes were assessed using metabolomics. Bulbs were dried using either microwave, air drying, or freeze drying and further subjected to chemical analysis of their composition of volatile and non-volatile metabolites. Volatiles were collected using solid phase micro-extraction (SPME coupled to gas chromatography–mass spectrometry (GC/MS with 42 identified volatiles including 30 sulphur compounds, four nitriles, three aromatics, and three esters. Profiling of the polar non-volatile metabolites via ultra-performance liquid chromatography coupled to high resolution MS (UPLC/MS annotated 51 metabolites including dipeptides, flavonoids, phenolic acids, and fatty acids. Major peaks in GC/MS or UPLC/MS contributing to the discrimination between A. sativum and A. cepa red cv. were assigned to sulphur compounds and flavonoids. Whereas sulphur conjugates amounted to the major forms in A. sativum, flavonoids predominated in the chemical composition of A. cepa red cv. With regard to drying impact on Allium metabolites, notable and clear separations among specimens were revealed using principal component analysis (PCA. The PCA scores plot of the UPLC/MS dataset showed closer metabolite composition of microwave dried specimens to freeze dried ones, and distant from air dried bulbs, observed in both A. cepa and A. sativum. Compared to GC/MS, the UPLC/MS derived PCA model was more consistent and better in assessing the impact of drying on Allium metabolism. A phthalate derivative was found exclusively in a commercial garlic preparation via GC/MS, of yet unknown origin. The freeze dried samples of both Allium species exhibited stronger antimicrobial activities compared to

  3. MetPP: a computational platform for comprehensive two-dimensional gas chromatography time-of-flight mass spectrometry-based metabolomics.

    Science.gov (United States)

    Wei, Xiaoli; Shi, Xue; Koo, Imhoi; Kim, Seongho; Schmidt, Robin H; Arteel, Gavin E; Watson, Walter H; McClain, Craig; Zhang, Xiang

    2013-07-15

    Due to the high complexity of metabolome, the comprehensive 2D gas chromatography time-of-flight mass spectrometry (GC×GC-TOF MS) is considered as a powerful analytical platform for metabolomics study. However, the applications of GC×GC-TOF MS in metabolomics are not popular owing to the lack of bioinformatics system for data analysis. We developed a computational platform entitled metabolomics profiling pipeline (MetPP) for analysis of metabolomics data acquired on a GC×GC-TOF MS system. MetPP can process peak filtering and merging, retention index matching, peak list alignment, normalization, statistical significance tests and pattern recognition, using the peak lists deconvoluted from the instrument data as its input. The performance of MetPP software was tested with two sets of experimental data acquired in a spike-in experiment and a biomarker discovery experiment, respectively. MetPP not only correctly aligned the spiked-in metabolite standards from the experimental data, but also correctly recognized their concentration difference between sample groups. For analysis of the biomarker discovery data, 15 metabolites were recognized with significant concentration difference between the sample groups and these results agree with the literature results of histological analysis, demonstrating the effectiveness of applying MetPP software for disease biomarker discovery. The source code of MetPP is available at http://metaopen.sourceforge.net xiang.zhang@louisville.edu Supplementary data are available at Bioinformatics online.

  4. Metabolic Effects of a 24-Week Energy-Restricted Intervention Combined with Low or High Dairy Intake in Overweight Women: An NMR-Based Metabolomics Investigation

    Directory of Open Access Journals (Sweden)

    Hong Zheng

    2016-02-01

    Full Text Available We investigated the effect of a 24-week energy-restricted intervention with low or high dairy intake (LD or HD on the metabolic profiles of urine, blood and feces in overweight/obese women by NMR spectroscopy combined with ANOVA-simultaneous component analysis (ASCA. A significant effect of dairy intake was found on the urine metabolome. HD intake increased urinary citrate, creatinine and urea excretion, and decreased urinary excretion of trimethylamine-N-oxide (TMAO and hippurate relative to the LD intake, suggesting that HD intake was associated with alterations in protein catabolism, energy metabolism and gut microbial activity. In addition, a significant time effect on the blood metabolome was attributed to a decrease in blood lipid and lipoprotein levels due to the energy restriction. For the fecal metabolome, a trend for a diet effect was found and a series of metabolites, such as acetate, butyrate, propionate, malonate, cholesterol and glycerol tended to be affected. Overall, even though these effects were not accompanied by a higher weight loss, the present metabolomics data reveal that a high dairy intake is associated with endogenous metabolic effects and effects on gut microbial activity that potentially impact body weight regulation and health. Moreover, ASCA has a great potential for exploring the effect of intervention factors and identifying altered metabolites in a multi-factorial metabolomic study.

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

    Directory of Open Access Journals (Sweden)

    Ming-Hui Li

    2017-07-01

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

  6. Mass Spectrometry-Based Metabolomic and Lipidomic Analyses of the Effects of Dietary Platycodon grandiflorum on Liver and Serum of Obese Mice under a High-Fat Diet

    Directory of Open Access Journals (Sweden)

    Hye Min Park

    2017-01-01

    Full Text Available We aimed to identify metabolites involved in the anti-obesity effects of Platycodon grandiflorum (PG in high-fat diet (HFD-fed mice using mass spectrometry (MS-based metabolomic techniques. C57BL/6J mice were divided into four groups: normal diet (ND-fed mice, HFD-fed mice, HFD with 1% PG extract-fed mice (HPGL, and HFD with 5% PG extract-fed mice (HPGH. After 8 weeks, the HFD group gained more weight than the ND group, while dietary 5% PG extract attenuated this change. The partial least squares discriminant analysis (PLS-DA score plots showed a clear distinction between experimental groups in serum and liver markers. We also identified 10 and 32 metabolites in the serum and liver, respectively, as potential biomarkers that could explain the effect of high-dose PG added to HFD-fed mice, which were strongly involved in amino acid metabolism (glycine, serine, threonine, methionine, glutamate, phenylalanine, ornithine, lysine, and tyrosine, TCA cycle (fumarate and succinate, lipid metabolism (linoleic and oleic acid methyl esters, oleamide, and cholesterol, purine/pyrimidine metabolism (uracil and hypoxanthine, carbohydrate metabolism (maltose, and glycerophospholipid metabolism (phosphatidylcholines, phosphatidylethanolamines, lysophosphatidylcholines, and lysophosphatidylethanolamines. We suggest that further studies on these metabolites could help us gain a better understanding of both HFD-induced obesity and the effects of PG.

  7. Metabolomics Study of Roux-en-Y Gastric Bypass Surgery (RYGB) to Treat Type 2 Diabetes Patients Based on Ultraperformance Liquid Chromatography-Mass Spectrometry.

    Science.gov (United States)

    Luo, Ping; Yu, Haoyong; Zhao, Xinjie; Bao, Yuqian; Hong, Christopher S; Zhang, Pin; Tu, Yinfang; Yin, Peiyuan; Gao, Peng; Wei, Li; Zhuang, Zhengping; Jia, Weiping; Xu, Guowang

    2016-04-01

    Roux-en-Y gastric bypass (RYGB) is one of the most effective treatments for long-term weight loss and diabetes remission; however, the mechanisms underlying these changes are not clearly understood. In this study, the serum metabolic profiles of 23 remission and 12 nonremission patients with type 2 diabetes mellitus (T2DM) were measured at baseline, 6- and 12-months after RYGB. A metabolomics analysis was performed based on ultra-performance liquid chromatography-mass spectrometry. Clinical improvements in insulin sensitivity, energy metabolism, and inflammation were related to metabolic alterations of free fatty acids (FFAs), acylcarnitines, amino acids, bile acids, and lipids species. Differential metabolic profiles were observed between the two T2DM subgroups, and patients with severity fat accumulation and oxidation stress may be more suitable for RYGB. Baseline levels of tryptophan, bilirubin, and indoxyl sulfate measured prior to surgery as well as levels of FFA 16:0, FFA 18:3, FFA 17:2, and hippuric acid measured at 6 months after surgery best predicted the suitability and efficacy of RYGB for patients with T2DM. These metabolites represent potential biomarkers that may be clinically helpful in individualized treatment for T2DM patients by RYGB.

  8. Investigation of the preventive effect of Sijunzi decoction on mitomycin C-induced immunotoxicity in rats by 1H NMR and MS-based untargeted metabolomic analysis.

    Science.gov (United States)

    Guan, Zhibo; Wu, Juan; Wang, Cancan; Zhang, Fang; Wang, Yinan; Wang, Miao; Zhao, Min; Zhao, Chunjie

    2018-01-10

    Sijunzi decoction (SJZD) is a well known traditional Chinese prescription used for the treatment of gastrointestinal disorders and immunity enhancement. It has been found to indeed improve life quality of chemotherapy patients and extensive used in clinical conbined with chemotherapeutics for the treatment of cancer. The aim of this study was to investigate the preventive effect of the immunotoxicity of SJZD on mitomycin C (MMC) and the metabolic mechanism of action. NMR and MS-based metabolomics approaches were combined for monitoring MMC-induced immunotoxicity and the protective effect of SJZD. Body weight change and mortality, histopathological observations and relative viscera weight determinations of spleen and thymus, sternum micronucleus assay and hematological analysis were used to confirm the immunotoxicity and attenuation effects. An OPLS-DA approach was used to screen potential biomarkers of immunotoxicity and the MetaboAnalyst and KEGG PATHWAY Database were used to investigate the metabolic pathways. 8 biomarkers in plasma samples, 19 in urine samples and 10 in spleen samples were identified as being primarily involved in amino acid metabolism, carbohydrate metabolism and lipid metabolism. The most critical pathway was alanine, aspartate and glutamate metabolism. The variations in biomarkers revealed the preventive effect of the immunotoxicity of SJZD on MMC and significant for speculating the possible metabolic mechanism. Copyright © 2017 Elsevier Ireland Ltd. All rights reserved.

  9. Hazard identification based on plant functional modelling

    International Nuclear Information System (INIS)

    Rasmussen, B.; Whetton, C.

    1993-10-01

    A major objective of the present work is to provide means for representing a process plant as a socio-technical system, so as to allow hazard identification at a high level. The method includes technical, human and organisational aspects and is intended to be used for plant level hazard identification so as to identify critical areas and the need for further analysis using existing methods. The first part of the method is the preparation of a plant functional model where a set of plant functions link together hardware, software, operations, work organisation and other safety related aspects of the plant. The basic principle of the functional modelling is that any aspect of the plant can be represented by an object (in the sense that this term is used in computer science) based upon an Intent (or goal); associated with each Intent are Methods, by which the Intent is realized, and Constraints, which limit the Intent. The Methods and Constraints can themselves be treated as objects and decomposed into lower-level Intents (hence the procedure is known as functional decomposition) so giving rise to a hierarchical, object-oriented structure. The plant level hazard identification is carried out on the plant functional model using the Concept Hazard Analysis method. In this, the user will be supported by checklists and keywords and the analysis is structured by pre-defined worksheets. The preparation of the plant functional model and the performance of the hazard identification can be carried out manually or with computer support. (au) (4 tabs., 10 ills., 7 refs.)

  10. Plant viral vectors based on tobamoviruses.

    Science.gov (United States)

    Yusibov, V; Shivprasad, S; Turpen, T H; Dawson, W; Koprowski, H

    1999-01-01

    The potential of plant virus-based transient expression vectors is substantial. One objective is the production of large quantities of foreign peptides or proteins. At least one commercial group (Biosource Technologies) is producing large quantities of product in the field, has built factories to process truck-loads of material and soon expects to market virus-generated products. In the laboratory, large amounts of protein have been produced for structural or biochemical analyses. An important aspect of producing large amounts of a protein or peptide is to make the product easily purifiable. This has been done by attaching peptides or proteins to easily purified units such as virion particles or by exporting proteins to the apoplast so that purification begins with a highly enriched product. For plant molecular biology, virus-based vectors have been useful in identifying previously unknown genes by overexpression or silencing or by expression in different genotypes. Also, foreign peptides fused to virions are being used as immunogens for development of antisera for experimental use or as injected or edible vaccines for medical use. As with liposomes and microcapsules, plant cells and plant viruses are also expected to provide natural protection for the passage of antigen through the gastrointestinal tract. Perhaps the greatest advantage of plant virus-based transient expression vectors is their host, plants. For the production of large amounts of commercial products, plants are one of the most economical and productive sources of biomass. They also present the advantages of lack of contamination with animal pathogens, relative ease of genetic manipulation and the presence eukaryotic protein modification machinery.

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

    Directory of Open Access Journals (Sweden)

    Msizi Innocent Mhlongo

    2016-10-01

    Full Text Available Metabolomics has developed into a valuable tool for advancing our understanding of plant metabolism. Plant innate immune defenses can be activated and enhanced so that, subsequent to being pre-sensitized, plants are able to launch a stronger and faster defense response upon exposure to pathogenic microorganisms, a phenomenon known as priming. Here, three contrasting chemical activators, namely acibenzolar-S-methyl, azelaic acid and riboflavin, were used to induce a primed state in Nicotiana tabacum cells. Identified biomarkers were then compared to responses induced by three phytohormones - abscisic acid, methyljasmonate and salicylic acid. Altered metabolomes were studied using a metabolite fingerprinting approach based on liquid chromatography and mass spectrometry. Multivariate data models indicated that these inducers cause time-dependent metabolic perturbations in the cultured cells and revealed biomarkers of which the levels are affected by these agents. A total of 34 metabolites were annotated from the mass spectral data and online databases. Venn diagrams were used to identify common biomarkers as well as those unique to a specific agent. Results implicate 20 cinnamic acid derivatives conjugated to (i quinic acid (chlorogenic acids, (ii tyramine, (iii polyamines or (iv glucose as discriminatory biomarkers of priming in tobacco cells. Functional roles for most of these metabolites in plant defense responses could thus be proposed. Metabolites induced by the activators belong to the early phenylpropanoid pathway, which indicates that different stimuli can activate similar pathways but with different metabolite fingerprints. Possible linkages to phytohormone-dependent pathways at a metabolomic level were indicated in the case of cells treated with salicylic acid and methyljasmonate. The results contribute to a better understanding of the priming phenomenon and advance our knowledge of cinnamic acid derivatives as versatile defense

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

    Science.gov (United States)

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

    2018-01-05

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

  13. NMR-based metabolomic profiling of overweight adolescents – an elucidation of the effects of inter-/intra-individual differences, gender, pubertal development and physical activity

    DEFF Research Database (Denmark)

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

    2014-01-01

    The plasma and urine metabolome of 192 overweight 12-15-year-old adolescents (BMI of 25.4 ± 2.3 kg/m(2)) were examined in order to elucidate gender, pubertal development measured as Tanner stage, physical activity measured as number of steps taken daily, and intra-/interindividual differences...... in the metabolome are being commenced already in childhood. The relationship between Tanner stage and the metabolome showed that pubertal development stage was positively related to urinary creatinine excretion and negatively related to urinary citrate content. No relations between physical activity...... and life-style related diseases. While this study is preliminary, these results may have the potential to translate into clinical applicability upon further investigations; if biomarkers for Tanner stage can be established, these might be used for identification of individuals susceptible to an early...

  14. Galaxy-M: a Galaxy workflow for processing and analyzing direct infusion and liquid chromatography mass spectrometry-based metabolomics data.

    Science.gov (United States)

    Davidson, Robert L; Weber, Ralf J M; Liu, Haoyu; Sharma-Oates, Archana; Viant, Mark R

    2016-01-01

    Metabolomics is increasingly recognized as an invaluable tool in the biological, medical and environmental sciences yet lags behind the methodological maturity of other omics fields. To achieve its full potential, including the integration of multiple omics modalities, the accessibility, standardization and reproducibility of computational metabolomics tools must be improved significantly. Here we present our end-to-end mass spectrometry metabolomics workflow in the widely used platform, Galaxy. Named Galaxy-M, our workflow has been developed for both direct infusion mass spectrometry (DIMS) and liquid chromatography mass spectrometry (LC-MS) metabolomics. The range of tools presented spans from processing of raw data, e.g. peak picking and alignment, through data cleansing, e.g. missing value imputation, to preparation for statistical analysis, e.g. normalization and scaling, and principal components analysis (PCA) with associated statistical evaluation. We demonstrate the ease of using these Galaxy workflows via the analysis of DIMS and LC-MS datasets, and provide PCA scores and associated statistics to help other users to ensure that they can accurately repeat the processing and analysis of these two datasets. Galaxy and data are all provided pre-installed in a virtual machine (VM) that can be downloaded from the GigaDB repository. Additionally, source code, executables and installation instructions are available from GitHub. The Galaxy platform has enabled us to produce an easily accessible and reproducible computational metabolomics workflow. More tools could be added by the community to expand its functionality. We recommend that Galaxy-M workflow files are included within the supplementary information of publications, enabling metabolomics studies to achieve greater reproducibility.

  15. Investigation of the chemomarkers correlated with flower colour in different organs of Catharanthus roseus using NMR-based metabolomics.

    Science.gov (United States)

    Pan, Qifang; Dai, Yuntao; Nuringtyas, Tri Rini; Mustafa, Natali Rianika; Schulte, Anna Elisabeth; Verpoorte, Robert; Choi, Young Hae

    2014-01-01

    Flower colour is a complex phenomenon that involves a wide range of secondary metabolites of flowers, for example phenolics and carotenoids as well as co-pigments. Biosynthesis of these metabolites, though, occurs through complicated pathways in many other plant organs. The analysis of the metabolic profile of leaves, stems and roots, for example, therefore may allow the identification of chemomarkers related to the final expression of flower colour. To investigate the metabolic profile of leaves, stems, roots and flowers of Catharanthus roseus and the possible correlation with four flower colours (orange, pink, purple and red). (1) H-NMR and multivariate data analysis were used to characterise the metabolites in the organs. The results showed that flower colour is characterised by a special pattern of metabolites such as anthocyanins, flavonoids, organic acids and sugars. The leaves, stems and roots also exhibit differences in their metabolic profiles according to the flower colour. Plants with orange flowers featured a relatively high level of kaempferol analogues in all organs except roots. Red-flowered plants showed a high level of malic acid, fumaric acid and asparagine in both flowers and leaves, and purple and pink flowering plants exhibited high levels of sucrose, glucose and 2,3-dihydroxy benzoic acid. High concentrations of quercetin analogues were detected in flowers and leaves of purple-flowered plants. There is a correlation between the metabolites specifically associated to the expression of different flower colours and the metabolite profile of other plant organs and it is therefore possible to predict the flower colours by detecting specific metabolites in leaves, stems or roots. This may have interesting application in the plant breeding industry. Copyright © 2013 John Wiley & Sons, Ltd.

  16. A Market-Based Virtual Power Plant

    DEFF Research Database (Denmark)

    You, Shi; Træholt, Chresten; Poulsen, Bjarne

    2009-01-01

    The fast growing penetration of Distributed Energy Resources (DER) and the continuing trend towards a more liberalized electricity market requires more efficient energy management strategies to handle both emerging technical and economic issues. In this paper, a market-based Virtual Power Plant...... demonstrates the potential benefits and operation scenarios of the MBVPP model....

  17. Plant Genome DataBase Japan (PGDBj).

    Science.gov (United States)

    Nakaya, Akihiro; Ichihara, Hisako; Asamizu, Erika; Shirasawa, Sachiko; Nakamura, Yasukazu; Tabata, Satoshi; Hirakawa, Hideki

    2017-01-01

    A portal website that integrates a variety of information related to genomes of model and crop plants from databases (DBs) and the literature was generated. This website, named the Plant Genome DataBase Japan (PGDBj, http://pgdbj. jp/en/ ), is comprised of three component DBs and a cross-search engine which provides a seamless search over their contents. One of the three component DBs is the Ortholog DB, which provides gene cluster information based on the amino acid sequence similarity. Over 1,000,000 amino acid sequences of 40 Viridiplantae species were collected from the public DNA DBs, and plant genome DBs such as TAIR and RAP-DB were subjected to reciprocal BLAST searches for clustering. Another component DB is the Plant Resource DB for genomic- and bio-resources. This DB also integrates the SABRE DB, which provides cDNA and genome sequence resources maintained in the RIKEN BioResource Center and National BioResource Projects Japan. The third component DB of PGDBj is the DNA Marker DB, which manually or automatically collects curated information on DNA markers, quantitative trait loci (QTL), and related genetic linkage maps, from the literature and external DBs. By combining these component DBs and a cross-search engine, PGDBj serves as a useful platform to study genetic systems for both fundamental and applied researches for a wide range of plant species.

  18. Licensed bases management for advanced nuclear plants

    International Nuclear Information System (INIS)

    O'Connell, J.; Rumble, E.; Rodwell, E.

    2001-01-01

    Prospective Advanced Nuclear Plant (ANP) owners must have high confidence that the integrity of the licensed bases (LB) of a plant will be effectively maintained over its life cycle. Currently, licensing engineers use text retrieval systems, database managers, and checklists to access, update, and maintain vast and disparate licensing information libraries. This paper describes the demonstration of a ''twin-engine'' approach that integrates a program from the emerging class of concept searching tools with a modern Product Data Management System (PDMS) to enhance the management of LB information for an example ANP design. (author)

  19. Nephron Toxicity Profiling via Untargeted Metabolome Analysis Employing a High Performance Liquid Chromatography-Mass Spectrometry-based Experimental and Computational Pipeline

    NARCIS (Netherlands)

    Ranninger, Christina; Rurik, Marc; Limonciel, Alice; Ruzek, Silke; Reischl, Roland; Wilmes, Anja; Jennings, Paul; Hewitt, Philip; Dekant, Wolfgang; Kohlbacher, Oliver; Huber, Christian G

    2015-01-01

    Untargeted metabolomics has the potential to improve the predictivity of in vitro toxicity models and therefore may aid the replacement of expensive and laborious animal models. Here we describe a long term repeat dose nephrotoxicity study conducted on the human renal proximal tubular epithelial

  20. Metabolomics technologies applied to the identification of compounds in plants : a liquid chromatography-mass spectrometry - nuclear magnetic resonance perspective over the tomato fruit

    NARCIS (Netherlands)

    Moco, S.I.A.

    2007-01-01

    A new era of plant biochemistry at the systems level is emerging in which the detailed description of biochemical phenomena, at the cellular level, is important for a better understanding of physiological, developmental, and biomolecular processes in plants. This emerging field is oriented towards

  1. Analytical error reduction using single point calibration for accurate and precise metabolomic phenotyping

    NARCIS (Netherlands)

    Kloet, F.M. van der; Bobeldijk, I.; Verheij, E.R.; Jellema, R.H.

    2009-01-01

    Analytical errors caused by suboptimal performance of the chosen platform for a number of metabolites and instrumental drift are a major issue in large-scale metabolomics studies. Especially for MS-based methods, which are gaining common ground within metabolomics, it is difficult to control the

  2. NMR-based metabolomics to determine acute inhalation effects of nano- and fine-sized ZnO particles in the rat lung.

    Science.gov (United States)

    Lee, Sheng-Han; Wang, Ting-Yi; Hong, Jia-Huei; Cheng, Tsun-Jen; Lin, Ching-Yu

    2016-09-01

    Zinc oxide (ZnO) particles induce acute occupational inhalation illness in humans and rats. However, the possible molecular mechanisms of ZnO particles on the respiratory system remain unclear. In this study, metabolic responses of the respiratory system of rats inhaled ZnO particles were investigated by a nuclear magnetic resonance (NMR)-based metabolomic approach. Male Sprague-Dawley rats were treated with a series of doses of nano-sized (35 nm) or fine-sized (250 nm) ZnO particles. The corresponding control groups inhaled filtered air. After 24 h, bronchoalveolar lavage fluid (BALF) and lung tissues were collected, extracted and prepared for (1)H and J-resolved NMR analysis, followed by principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA). PCA and PLSDA models from analysis of BALF and hydrophilic lung NMR spectra demonstrated that dose response trends were restricted to the 250 nm ZnO particle exposure group and were not observed in the 35 nm ZnO particle exposure group. Increased isoleucine and valine, as well as decreased acetate, trimethylamine n-oxide, taurine, glycine, formate, ascorbate and glycerophosphocholine, were recorded in the BALF of rats treated with moderate and high dose 250 nm ZnO exposures. Decreases in taurine and glucose, as well as an increase of phosphorylcholine-containing lipids and fatty acyl chains, were detected in the lung tissues from 250 nm ZnO-treated rats. These metabolic changes may be associated with cell anti-oxidation, energy metabolism, DNA damage and membrane stability. We also concluded that a metabolic approach provides more complete measurements and suggests potential molecular mechanisms of adverse effects.

  3. Metabolomics Workbench (MetWB)

    Data.gov (United States)

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

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

    Science.gov (United States)

    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.

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

    Science.gov (United States)

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

    2009-02-01

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

  6. Metabolomic Responses of Guard Cells and Mesophyll Cells to Bicarbonate

    Science.gov (United States)

    Misra, Biswapriya B.; de Armas, Evaldo; Tong, Zhaohui; Chen, Sixue

    2015-01-01

    Anthropogenic CO2 presently at 400 ppm is expected to reach 550 ppm in 2050, an increment expected to affect plant growth and productivity. Paired stomatal guard cells (GCs) are the gate-way for water, CO2, and pathogen, while mesophyll cells (MCs) represent the bulk cell-type of green leaves mainly for photosynthesis. We used the two different cell types, i.e., GCs and MCs from canola (Brassica napus) to profile metabolomic changes upon increased CO2 through supplementation with bicarbonate (HCO3 -). Two metabolomics platforms enabled quantification of 268 metabolites in a time-course study to reveal short-term responses. The HCO3 - responsive metabolomes of the cell types differed in their responsiveness. The MCs demonstrated increased amino acids, phenylpropanoids, redox metabolites, auxins and cytokinins, all of which were decreased in GCs in response to HCO3 -. In addition, the GCs showed differential increases of primary C-metabolites, N-metabolites (e.g., purines and amino acids), and defense-responsive pathways (e.g., alkaloids, phenolics, and flavonoids) as compared to the MCs, indicating differential C/N homeostasis in the cell-types. The metabolomics results provide insights into plant responses and crop productivity under future climatic changes where elevated CO2 conditions are to take center-stage. PMID:26641455

  7. Quality Evaluation of Panax ginseng Roots Using a Rapid Resolution LC-QTOF/MS-Based Metabolomics Approach

    Directory of Open Access Journals (Sweden)

    Dae-Young Lee

    2013-12-01

    Full Text Available Korean ginseng (Panax ginseng C.A. Meyer contains several types of ginsenosides, which are considered the major active medicinal components of ginseng. The types and quantities of ginsenosides found in ginseng may differ, depending on the location of cultivation, making it necessary to establish a reliable method for distinguishing cultivation locations of ginseng roots. P. ginseng roots produced in different regions of Korea, China, and Japan have been unintentionally confused in herbal markets owing to their complicated plant sources. PCA and PLS-DA using RRLC-QTOF/MS data was able to differentiate between ginsengs cultivated in Korea, China, and Japan. The chemical markers accountable for such variations were identified through a PCA loadings plot, tentatively identified by RRLC-QTOF/MS and partially verified by available reference standards. The classification result can be used to identify P. ginseng origin.

  8. “Omics” Prospective Monitoring of Bariatric Surgery: Roux-En-Y Gastric Bypass Outcomes Using Mixed-Meal Tolerance Test and Time-Resolved 1H NMR-Based Metabolomics

    Science.gov (United States)

    Lopes, Thiago I.B.; Geloneze, Bruno; Pareja, José C.; Calixto, Antônio R.; Ferreira, Márcia M.C.

    2016-01-01

    Abstract Roux-en-Y gastric bypass (RYGB) surgery goes beyond weight loss to induce early beneficial hormonal changes that favor glycemic control. In this prospective study, ten obese subjects diagnosed with type 2 diabetes underwent bariatric surgery. Mixed-meal tolerance test was performed before and 12 months after RYGB, and the outcomes were investigated by a time-resolved hydrogen nuclear magnetic resonance (1H NMR)-based metabolomics. To the best of our knowledge, no previous omics-driven study has used time-resolved 1H NMR-based metabolomics to investigate bariatric surgery outcomes. Our results presented here show a significant decrease in glucose levels after bariatric surgery (from 159.80 ± 61.43 to 100.00 ± 22.94 mg/dL), demonstrating type 2 diabetes remission (p < 0.05). The metabolic profile indicated lower levels of lactate, alanine, and branched chain amino acids for the operated subject at fasting state after the surgery. However, soon after food ingestion, the levels of these metabolites increased faster in operated than in nonoperated subjects. The lipoprotein profile achieved before and after RYGB at fasting was also significantly different, but converging 180 min after food ingestion. For example, the very low-density lipoprotein, low-density lipoprotein, N-acetyl-glycoproteins, and unsaturated lipid levels decreased after RYGB, while phosphatidylcholine and high-density lipoprotein increased. This study provides important insights on RYGB surgery and attendant type 2 diabetes outcomes using an “omics” systems science approach. Further research on metabolomic correlates of RYGB surgery in larger study samples is called for. PMID:27428253

  9. Plant-based Rasayana drugs from Ayurveda.

    Science.gov (United States)

    Balasubramani, Subramani Paranthaman; Venkatasubramanian, Padma; Kukkupuni, Subrahmanya Kumar; Patwardhan, Bhushan

    2011-02-01

    Rasayana tantra is one of the eight specialties of Ayurveda. It is a specialized practice in the form of rejuvenative recipes, dietary regimen, special health promoting behaviour and drugs. Properly administered Rasayana can bestow the human being with several benefits like longevity, memory, intelligence, freedom from diseases, youthful age, excellence of luster, complexion and voice, optimum strength of physique and sense organs, respectability and brilliance. Various types of plant based Rasayana recipes are mentioned in Ayurveda. Review of the current literature available on Rasayanas indicates that anti-oxidant and immunomodulation are the most studied activities of the Rasayana drugs. Querying in Pubmed database on Rasayanas reveals that single plants as well as poly herbal formulations have been researched on. This article reviews the basics of Rasayana therapy and the published research on different Rasayana drugs for specific health conditions. It also provides the possible directions for future research.

  10. Non-target effects of GM potato : an eco-metabolomics approach

    NARCIS (Netherlands)

    Plischke, Andreas

    2013-01-01

    In this thesis, patterns of variation in plant metabolomes and insect communities were described in GM and non-GM potato plants in both laboratory and field experiments. Differences between plant genotypes in insect abundances were small when compared to year-to-year differences, location effects

  11. {sup 1}H NMR-based metabolomics reveals sub-lethal toxicity of a mixture of diabetic and lipid-regulating pharmaceuticals on amphibian larvae

    Energy Technology Data Exchange (ETDEWEB)

    Melvin, Steven D., E-mail: s.melvin@griffith.edu.au [Australian Rivers Institute, Griffith University, Southport, QLD 4222 (Australia); Habener, Leesa J. [Griffith School of Environment, Griffith University, Southport, QLD 4222 (Australia); Leusch, Frederic D.L. [Australian Rivers Institute, Griffith University, Southport, QLD 4222 (Australia); Griffith School of Environment, Griffith University, Southport, QLD 4222 (Australia); Carroll, Anthony R. [Griffith School of Environment, Griffith University, Southport, QLD 4222 (Australia)

    2017-03-15

    Highlights: • Pharmaceutical pollutants are a concern for eliciting adverse effects in wildlife. • Diabetes and lipid regulating drugs are widely used and poorly removed from sewage. • We explored the toxicity of a mixture of metformin, atorvastatin and bezafibrate on tadpoles. • Exposure caused increased growth and development but no effects on lipids or cholesterol. • {sup 1}H NMR-based metabolomics reveal increased lactic acid and BCAAs in exposed animals. - Abstract: Pharmaceuticals are widely used for the treatment of various physical and psychological ailments. Due to incomplete removal during sewage treatment many pharmaceuticals are frequently detected in aquatic waterways at trace concentrations. The diversity of pharmaceutical contaminants and potential for complex mixtures to occur makes it very difficult to predict the toxicity of these compounds on wildlife, and robust methods are therefore needed to explore sub-lethal effects. Metabolic syndrome is one of the most widespread health concerns currently facing the human population, and various drugs, including anti-diabetic medications and lipid- and cholesterol-lowering fibrates and statins, are widely prescribed as treatment. In this study, we exposed striped marsh frog (Limnodynastes peronii) tadpoles to a mixture of the drugs metformin, atorvastatin and bezafibrate at 0.5, 5, 50 and 500 μg/L to explore possible effects on growth and development, energy reserves (triglycerides and cholesterol), and profiles of small polar metabolites extracted from hepatic tissues. It was hypothesised that exposure would result in a general reduction in energy reserves, and that this would subsequently correspond with reduced growth and development. Responses differed from expected outcomes based on the known mechanisms of these compounds in humans, with no changes to hepatic triglycerides or cholesterol and a general increase in mass and condition with increasing exposure concentration. Deviation from the

  12. 1H NMR-based metabolomics reveals sub-lethal toxicity of a mixture of diabetic and lipid-regulating pharmaceuticals on amphibian larvae

    International Nuclear Information System (INIS)

    Melvin, Steven D.; Habener, Leesa J.; Leusch, Frederic D.L.; Carroll, Anthony R.

    2017-01-01

    Highlights: • Pharmaceutical pollutants are a concern for eliciting adverse effects in wildlife. • Diabetes and lipid regulating drugs are widely used and poorly removed from sewage. • We explored the toxicity of a mixture of metformin, atorvastatin and bezafibrate on tadpoles. • Exposure caused increased growth and development but no effects on lipids or cholesterol. • 1 H NMR-based metabolomics reveal increased lactic acid and BCAAs in exposed animals. - Abstract: Pharmaceuticals are widely used for the treatment of various physical and psychological ailments. Due to incomplete removal during sewage treatment many pharmaceuticals are frequently detected in aquatic waterways at trace concentrations. The diversity of pharmaceutical contaminants and potential for complex mixtures to occur makes it very difficult to predict the toxicity of these compounds on wildlife, and robust methods are therefore needed to explore sub-lethal effects. Metabolic syndrome is one of the most widespread health concerns currently facing the human population, and various drugs, including anti-diabetic medications and lipid- and cholesterol-lowering fibrates and statins, are widely prescribed as treatment. In this study, we exposed striped marsh frog (Limnodynastes peronii) tadpoles to a mixture of the drugs metformin, atorvastatin and bezafibrate at 0.5, 5, 50 and 500 μg/L to explore possible effects on growth and development, energy reserves (triglycerides and cholesterol), and profiles of small polar metabolites extracted from hepatic tissues. It was hypothesised that exposure would result in a general reduction in energy reserves, and that this would subsequently correspond with reduced growth and development. Responses differed from expected outcomes based on the known mechanisms of these compounds in humans, with no changes to hepatic triglycerides or cholesterol and a general increase in mass and condition with increasing exposure concentration. Deviation from the

  13. Topsoil depth substantially influences the responses to drought of the foliar metabolomes of Mediterranean forests

    Energy Technology Data Exchange (ETDEWEB)

    Rivas-Ubach, Albert; Barbeta, Adrià; Sardans, Jordi; Guenther, Alex; Ogaya, Romà; Oravec, Michal; Urban, Otmar; Peñuelas, Josep

    2016-08-01

    Soils provide physical support, water, and nutrients to terrestrial plants. Upper soil layers are crucial for forest dynamics, especially under drought conditions, because many biological processes occur there and provide support, water and nutrients to terrestrial plants. We postulated that tree size and overall plant function manifested in the metabolome composition, the total set of metabolites, were dependent on the depth of upper soil layers and on water availability. We sampled leaves for stoichiometric and metabolomic analyses once per season from differently sized Quercus ilex trees under natural and experimental drought conditions as projected for the coming decades. Different sized trees had different metabolomes and plots with shallower soils had smaller trees. Soil moisture of the upper soil did not explain the tree size and smaller trees did not show higher concentrations of biomarker metabolites related to drought stress. However, the impact of drought treatment on metabolomes was higher in smaller trees in shallower soils. Our results suggested that tree size was more dependent on the depth of the upper soil layers, which indirectly affect the metabolomes of the trees, than on the moisture content of the upper soil layers. Metabolomic profiling of Q. ilex supported the premise that water availability in the upper soil layers was not necessarily correlated with tree size. The higher impact of drought on trees growing in shallower soils nevertheless indicates a higher vulnerability of small trees to the future increase in frequency, intensity, and duration of drought projected for the Mediterranean Basin and other areas. Metabolomics has proven to be an excellent tool detecting significant metabolic changes among differently sized individuals of the same species and it improves our understanding of the connection between plant metabolomes and environmental variables such as soil depth and moisture content.

  14. Serum Metabolomics in Rats after Acute Paraquat Poisoning.

    Science.gov (United States)

    Wang, Zhiyi; Ma, Jianshe; Zhang, Meiling; Wen, Congcong; Huang, Xueli; Sun, Fa; Wang, Shuanghu; Hu, Lufeng; Lin, Guanyang; Wang, Xianqin

    2015-01-01

    Paraquat is one of the most widely used herbicides in the world and is highly toxic to humans and animals. In this study, we developed a serum metabolomic method based on GC/MS to evaluate the effects of acute paraquat poisoning on rats. Pattern recognition analysis, including both principal component analysis and partial least squares-discriminate analysis revealed that acute paraquat poisoning induced metabolic perturbations. Compared with the control group, the level of octadecanoic acid, L-serine, L-threonine, L-valine, and glycerol in the acute paraquat poisoning group (36 mg/kg) increased, while the levels of hexadecanoic acid, D-galactose, and decanoic acid decreased. These findings provide an overview of systematic responses to paraquat exposure and metabolomic insight into the toxicological mechanism of paraquat. Our results indicate that metabolomic methods based on GC/MS may be useful to elucidate the mechanism of acute paraquat poisoning through the exploration of biomarkers.

  15. A Conversation on Data Mining Strategies in LC-MS Untargeted Metabolomics: Pre-Processing and Pre-Treatment Steps

    Directory of Open Access Journals (Sweden)

    Fidele Tugizimana

    2016-11-01

    Full Text Available Untargeted metabolomic studies generate information-rich, high-dimensional, and complex datasets that remain challenging to handle and fully exploit. Despite the remarkable progress in the development of tools and algorithms, the “exhaustive” extraction of information from these metabolomic datasets is still a non-trivial undertaking. A conversation on data mining strategies for a maximal information extraction from metabolomic data is needed. Using a liquid chromatography-mass spectrometry (LC-MS-based untargeted metabolomic dataset, this study explored the influence of collection parameters in the data pre-processing step, scaling and data transformation on the statistical models generated, and feature selection, thereafter. Data obtained in positive mode generated from a LC-MS-based untargeted metabolomic study (sorghum plants responding dynamically to infection by a fungal pathogen were used. Raw data were pre-processed with MarkerLynxTM software (Waters Corporation, Manchester, UK. Here, two parameters were varied: the intensity threshold (50–100 counts and the mass tolerance (0.005–0.01 Da. After the pre-processing, the datasets were imported into SIMCA (Umetrics, Umea, Sweden for more data cleaning and statistical modeling. In addition, different scaling (unit variance, Pareto, etc. and data transformation (log and power methods were explored. The results showed that the pre-processing parameters (or algorithms influence the output dataset with regard to the number of defined features. Furthermore, the study demonstrates that the pre-treatment of data prior to statistical modeling affects the subspace approximation outcome: e.g., the amount of variation in X-data that the model can explain and predict. The pre-processing and pre-treatment steps subsequently influence the number of statistically significant extracted/selected features (variables. Thus, as informed by the results, to maximize the value of untargeted metabolomic data

  16. Metabolomics Society’s International Affiliations

    NARCIS (Netherlands)

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

    2015-01-01

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

  17. Ultraperformance liquid chromatography-mass spectrometry based comprehensive metabolomics combined with pattern recognition and network analysis methods for characterization of metabolites and metabolic pathways from biological data sets.

    Science.gov (United States)

    Zhang, Ai-hua; Sun, Hui; Han, Ying; Yan, Guang-li; Yuan, Ye; Song, Gao-chen; Yuan, Xiao-xia; Xie, Ning; Wang, Xi-jun

    2013-08-06

    Metabolomics is the study of metabolic changes in biological systems and provides the small molecule fingerprints related to the disease. Extracting biomedical information from large metabolomics data sets by multivariate data analysis is of considerable complexity. Therefore, more efficient and optimizing metabolomics data processing technologies are needed to improve mass spectrometry applications in biomarker discovery. Here, we report the findings of urine metabolomic investigation of hepatitis C virus (HCV) patients by high-throughput ultraperformance liquid chromatography-mass spectrometry (UPLC-MS) coupled with pattern recognition methods (principal component analysis, partial least-squares, and OPLS-DA) and network pharmacology. A total of 20 urinary differential metabolites (13 upregulated and 7 downregulated) were identified and contributed to HCV progress, involve several key metabolic pathways such as taurine and hypotaurine metabolism, glycine, serine and threonine metabolism, histidine metabolism, arginine and proline metabolism, and so forth. Metabolites identified through metabolic profiling may facilitate the development of more accurate marker algorithms to better monitor disease progression. Network analysis validated close contact between these metabolites and implied the importance of the metabolic pathways. Mapping altered metabolites to KEGG pathways identified alterations in a variety of biological processes mediated through complex networks. These findings may be promising to yield a valuable and noninvasive tool that insights into the pathophysiology of HCV and to advance the early diagnosis and monitor the progression of disease. Overall, this investigation illustrates the power of the UPLC-MS platform combined with the pattern recognition and network analysis methods that can engender new insights into HCV pathobiology.

  18. Metabolomics reveals simultaneous influences of plant defence system and fungal growth in Botrytis cinerea-infected Vitis vinifera cv. Chardonnay berries.

    Science.gov (United States)

    Hong, Young-Shick; Martinez, Agathe; Liger-Belair, Gérard; Jeandet, Philippe; Nuzillard, Jean-Marc; Cilindre, Clara

    2012-10-01

    Botrytis cinerea is a fungal plant pathogen of grape berries, leading to economic and quality losses in wine production. The global metabolite changes induced by B. cinerea infection in grape have not been established to date, even though B. cinerea infection is known to cause significant changes in chemicals or metabolites. In order to better understand metabolic mechanisms linked to the infection process and to identify the metabolites associated with B. cinerea infection, (1)H NMR spectroscopy was used in global metabolite profiling and multivariate statistical analysis of berries from healthy and botrytized bunches. Pattern recognition methods, such as principal component analysis, revealed clear metabolic discriminations between healthy and botrytized berries of botrytized bunches and healthy berries of healthy bunches. Significantly high levels of proline, glutamate, arginine, and alanine, which are accumulated upon plant stress, were found in healthy and botrytized berries of botrytized bunches. Moreover, largely degraded phenylpropanoids, flavonoid compounds, and sucrose together with markedly produced glycerol, gluconic acid, and succinate, all being directly associated with B. cinerea growth, were only found in botrytized berries of botrytized bunches. This study reports that B. cinerea infection causes significant metabolic changes in grape berry and highlights that both the metabolic perturbations associated with the plant defence system and those directly derived from fungal pathogen growth should be considered to better understand the interaction between metabolic variation and biotic pathogen stress in plants.

  19. Risk-based plant performance indicators

    International Nuclear Information System (INIS)

    Boccio, J.L.; Azarm, M.A.; Hall, R.E.

    1991-01-01

    Tasked by the 1979 President's Commission on the Accident at Three Mile Island, the U.S. nuclear power industry has put into place a performance indicator program as one means for showing a demonstrable record of achievement. Largely through the efforts of the Institute of Nuclear Power Operations (INPO), plant performance data has, since 1983, been collected and analyzed to aid utility management in measuring their plants' performance progress. The U.S. Nuclear Regulatory Commission (NRC) has also developed a set of performance indicators. This program, conducted by NRC's Office for the Analysis and Evaluation of Operational Data (AEOD), is structured to present information on plant operational performance in a manner that could enhance the staff's ability to recognize changes in the safety performance. Both organizations recognized that performance indicators have limitations and could be subject to misinterpretation and misuse with the potential for an adverse impact on safety. This paper reports on performance indicators presently in use, e.g., unplanned automatic scrams, unplanned safety system actuation, safety system failures, etc., which are logically related to safety. But, a reliability/risk-based method for evaluating either individual indicators or an aggregated set of indicators is not yet available

  20. The future of metabolomics in ELIXIR [version 2; referees: 2 approved, 1 approved with reservations

    Directory of Open Access Journals (Sweden)

    Merlijn van Rijswijk

    2017-10-01

    Full Text Available 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. The future of metabolomics in ELIXIR [version 1; referees: 2 approved, 1 approved with reservations

    Directory of Open Access Journals (Sweden)

    Merlijn van Rijswijk

    2017-09-01

    Full Text Available 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.

  2. A new strategy of exploring metabolomics data using Monte Carlo tree.

    Science.gov (United States)

    Cao, Dong-Sheng; Wang, Bing; Zeng, Mao-Mao; Liang, Yi-Zeng; Xu, Qing-Song; Zhang, Liang-Xiao; Li, Hong-Dong; Hu, Qian-Nan

    2011-03-07

    Large amounts of data from high-throughput metabolomics experiments have become commonly more and more complex, which brings a number of challenges to existing statistical modeling. Thus there is a need to develop a statistically efficient approach for mining the underlying metabolite information contained by metabolomics data under investigation. In this work, we provide a new strategy based on Monte Carlo cross validation coupled with the classification tree algorithm, which is termed as the MCTree approach. The MCTree approach inherently provides a feasible way to uncover the predictive structure of metabolomics data by the establishment of many cross-predictive models. With the help of the sample proximity matrix such obtained, it seems to be able to give some interesting insights into metabolomics data. Simultaneously, informative metabolites or potential biomarkers can be successfully discovered by means of variable importance ranking in the MCTree approach. Two real metabolomics datasets are finally used to demonstrate the performance of the proposed approach.

  3. ECMDB: The E. coli Metabolome Database

    OpenAIRE

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

    2012-01-01

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

  4. Qualitative Alterations of Bacterial Metabolome after Exposure to Metal Nanoparticles with Bactericidal Properties: A Comprehensive Workflow Based on (1)H NMR, UHPLC-HRMS, and Metabolic Databases.

    Science.gov (United States)

    Chatzimitakos, Theodoros G; Stalikas, Constantine D

    2016-09-02

    Metal nanoparticles (NPs) have proven to be more toxic than bulk analogues of the same chemical composition due to their unique physical properties. The NPs, lately, have drawn the attention of researchers because of their antibacterial and biocidal properties. In an effort to shed light on the mechanism through which the bacteria elimination is achieved and the metabolic changes they undergo, an untargeted metabolomic fingerprint study was carried out on Gram-positive (Staphylococcus aureus) and Gram-negative (Escherichia coli) bacteria species. The (1)H NMR spectroscopy, in conjunction with high resolution mass-spectrometry (HRMS) and an unsophisticated data processing workflow were implemented. The combined NMR/HRMS data, supported by an open-access metabolomic database, proved to be efficacious in the process of assigning a putative annotation to a wide range of metabolite signals and is a useful tool to appraise the metabolome alterations, as a consequence of bacterial response to NPs. Interestingly, not all the NPs diminished the intracellular metabolites; bacteria treated with iron NPs produced metabolites not present in the nonexposed bacteria sample, implying the activation of previously inactive metabolic pathways. In contrast, copper and iron-copper NPs reduced the annotated metabolites, alluding to the conclusion that the metabolic pathways (mainly alanine, aspartate, and glutamate metabolism, beta-alanine metabolism, glutathione metabolism, and arginine and proline metabolism) were hindered by the interactions of NPs with the intracellular metabolites.

  5. UPLC-Q-TOF/MS-based metabolomic studies on the toxicity mechanisms of traditional Chinese medicine Chuanwu and the detoxification mechanisms of Gancao, Baishao, and Ganjiang.

    Science.gov (United States)

    Dong, Hui; Yan, Guang-Li; Han, Ying; Sun, Hui; Zhang, Ai-Hua; Li, Xian-Na; Wang, Xi-Jun

    2015-09-01

    Chuanwu (CW), a famous traditional Chinese medicine (TCM) from the mother roots of Aconitum carmichaelii Debx.. (Ranunculaceae), has been used for the treatment of various diseases. Unfortunately, its toxicity is frequently reported because of its narrow therapeutic window. In the present study, a metabolomic method was performed to characterize the phenotypically biochemical perturbations and potential mechanisms of CW-induced toxicity. Meanwhile, the expression level of toxicity biomarkers in the urine were analyzed to evaluate the detoxification by combination with Gancao (Radix Glyeyrrhizae, CG), Baishao (Radix Paeoniae Alba, CS) and Ganjiang (Rhizoma Zingiberis, CJ), which were screened from classical TCM prescriptions. Urinary metabolomics was performed by UPLC-Q-TOF-HDMS, and the mass spectra signals of the detected metabolites were systematically analyzed using pattern recognition methods. As a result, seventeen biomarkers associated with CW toxicity were identified, which were associated with pentose and glucuronate interconversions, alanine, aspartate, and glutamate metabolism, among others. The expression levels of most toxicity biomarkers were effectively modulated towards the normal range by the compatibility drugs. It indicated that the three compatibility drugs could effectively detoxify CW. In summary, our work demonstrated that metabolomics was vitally significant to evaluation of toxicity and finding detoxification methods for TCM. Copyright © 2015 China Pharmaceutical University. Published by Elsevier B.V. All rights reserved.

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

    Science.gov (United States)

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

    2017-12-01

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

  7. Metabolomics: the chemistry between ecology and genetics

    NARCIS (Netherlands)

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

    2010-01-01

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

  8. NMR-based metabolomics for simultaneously evaluating multiple determinants of primary beef quality in Japanese Black cattle

    OpenAIRE

    Kodani, Yoshinori; Miyakawa, Takuya; Komatsu, Tomohiko; Tanokura, Masaru

    2017-01-01

    Analytical methodologies to comprehensively evaluate beef quality are increasingly needed to accelerate improvement in both breeding and post-mortem processing. Consumer palatability towards beef is generally attributed to tenderness, flavor, and/or juiciness. These primary qualities are modified by post-mortem aging and the crude content and fatty acid composition of intramuscular fat. In this study, we report a nuclear magnetic resonance (NMR)-based metabolic profiles of Japanese Black catt...

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

    Science.gov (United States)

    Fearnley, Liam G; Inouye, Michael

    2016-10-01

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

  10. Metabolome analysis - mass spectrometry and microbial primary metabolites

    DEFF Research Database (Denmark)

    Højer-Pedersen, Jesper Juul

    2008-01-01

    increased amounts of data generated in high resolution. One major limitation though is the digestion of data coverting the information into a format that can be interpreted in a biological context and take metabolomics beyond the principle of guilt-byassociation. To analyze the data there is a general need....... Statistical analysis of the footprinting data revealed discriminating ions, which could be assigned using the in silico metabolome. By this approach metabolic footprinting can advance from a classification method that is used to derive biological information based on guilt-by-association, to a tool...

  11. NMR-based metabolomic investigation of bioactivity of chemical constituents in black raspberry (Rubus occidentalis L.) fruit extracts.

    Science.gov (United States)

    Paudel, Liladhar; Wyzgoski, Faith J; Giusti, M Monica; Johnson, Jodee L; Rinaldi, Peter L; Scheerens, Joseph C; Chanon, Ann M; Bomser, Joshua A; Miller, A Raymond; Hardy, James K; Reese, R Neil

    2014-02-26

    Black raspberry (Rubus occidentalis L.) (BR) fruit extracts with differing compound profiles have shown variable antiproliferative activities against HT-29 colon cancer cell lines. This study used partial least-squares (PLS) regression analysis to develop a high-resolution (1)H NMR-based multivariate statistical model for discerning the biological activity of BR constituents. This model identified specific bioactive compounds and ascertained their relative contribution against cancer cell proliferation. Cyanidin 3-rutinoside and cyanidin 3-xylosylrutinoside were the predominant contributors to the extract bioactivity, but salicylic acid derivatives (e.g., salicylic acid glucosyl ester), quercetin 3-glucoside, quercetin 3-rutinoside, p-coumaric acid, epicatechin, methyl ellagic acid derivatives (e.g., methyl ellagic acetyl pentose), and citric acid derivatives also contributed significantly to the antiproliferative activity of the berry extracts. This approach enabled the identification of new bioactive components in BR fruits and demonstrates the utility of the method for assessing chemopreventive compounds in foods and food products.

  12. Effect of pomegranate based marinades on the microbiological, chemical and sensory quality of chicken meat: A metabolomics approach.

    Science.gov (United States)

    Lytou, Anastasia E; Nychas, George-John E; Panagou, Efstathios Z

    2018-02-21

    Pomegranate juice is a product with enhanced functional properties that could be used as an alternative to traditional marination ingredients and effectively retard microbial growth along with providing an improved sensory result. In this study, two pomegranate based marinades were prepared for the marination of chicken breast fillets and the marinated samples were aerobically stored at 4 and 10°C for 9days. Raw, non-marinated chicken samples were used as control. Levels of total viable counts (TVC), Pseudomonas spp., Brochothrix thermosphacta, Enterobacteriaceae and lactic acid bacteria (LAB) were determined together with sensory assessment to evaluate the evolution of spoilage. The profile of organic acids and volatile compounds was also analyzed during storage. The shelf life of marinated samples was significantly extended compared to control samples at both storage temperatures (e.g., up to 5 and 6days for the pomegranate/lemon marinated samples stored at 4 and 10°C, respectively) as evaluated by both microbiological and sensory analyses. The profile of the organic acids and the volatilome of marinated and control samples were remarkably differentiated according to storage time, microbial load and sensory score. The findings of this study suggest that pomegranate juice could be used as a novel ingredient in marinades to improve the sensory attributes, while prolonging the shelf life of chicken meat. Copyright © 2017 Elsevier B.V. All rights reserved.

  13. Early Effect of Amyloid β-Peptide on Hippocampal and Serum Metabolism in Rats Studied by an Integrated Method of NMR-Based Metabolomics and ANOVA-Simultaneous Component Analysis

    Directory of Open Access Journals (Sweden)

    Yao Du

    2017-01-01

    Full Text Available Amyloid β (Aβ deposition has been implicated in the pathogenesis of Alzheimer’s disease. However, the early effect of Aβ deposition on metabolism remains unclear. In the present study, thus, we explored the metabolic changes in the hippocampus and serum during first 2 weeks of Aβ25–35 injection in rats by using an integrated method of NMR-based metabolomics and ANOVA-simultaneous component analysis (ASCA. Our results show that Aβ25–35 injection, time, and their interaction had statistically significant effects on the hippocampus and serum metabolome. Furthermore, we identified key metabolites that mainly contributed to these effects. After Aβ25–35 injection from 1 to 2 weeks, the levels of lactate, N-acetylaspartate, creatine, and taurine were decreased in rat hippocampus, while an increase in lactate and decreases in LDL/VLDL and glucose were observed in rat serum. Therefore, we suggest that the reduction in energy and lipid metabolism as well as an increase in anaerobic glycolysis may occur at the early stage of Aβ25–35 deposition.

  14. Metabolomic application in toxicity evaluation and toxicological biomarker identification of natural product.

    Science.gov (United States)

    Chen, Dan-Qian; Chen, Hua; Chen, Lin; Tang, Dan-Dan; Miao, Hua; Zhao, Ying-Yong

    2016-05-25

    Natural product plays a vital role in disease prevention and treatment since the appearance of civilization, but the toxicity severely hinders its wide use. In order to avoid toxic effect as far as possible and use natural product safely, more comprehensive understandings of toxicity are urgently required. Since the metabolome represents the physiological or pathological status of organisms, metabolomics-based toxicology is of significance to observe potential injury before toxins have caused physiological or pathological damages. Metabolomics-based toxicology can evaluate toxicity and identify toxicological biomarker of natural product, which is helpful to guide clinical medication and reduce adverse drug reactions. In the past decades, dozens of metabolomic researches have been implemented on toxicity evaluation, toxicological biomarker identification and potential mechanism exploration of nephrotoxicity, hepatotoxicity, cardiotoxicity and central nervous system toxicity induced by pure compounds, extracts and compound prescriptions. In this paper, metabolomic technology, sample preparation, data process and analysis, and metabolomics-based toxicological research of natural product are reviewed, and finally, the potential problems and further perspectives in toxicological metabolomic investigations of natural product are discussed. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

  15. Deep Learning Accurately Predicts Estrogen Receptor Status in Breast Cancer Metabolomics Data.

    Science.gov (United States)

    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 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.

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

    Science.gov (United States)

    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.

  17. A metabolomics approach to thrips resistance in tomato

    OpenAIRE

    Romero González, Roman Rodolfo

    2011-01-01

    Western flower thrips is one of the most serious crop pests worldwide. Its control relies mainly on pesticides whose excessive use leads to resistance development and environmental contamination. As an alternative, in this thesis host-plant resistance in wild and domesticated tomatoes was studied using metabolomics. Different resistance mechanisms in which mechanical and chemical defenses work coordinately to fend thrips off were observed and contrasted. In all cases resistance was associated...

  18. 1H NMR-Based Metabolomics Study of the Toxicological Effects in Rats Induced by “Renqing Mangjue” Pill, a Traditional Tibetan Medicine

    Directory of Open Access Journals (Sweden)

    Can Xu

    2017-09-01

    Full Text Available “RenqingMangjue” pill (RMP, as an effective prescription of Traditional Tibetan Medicine (TTM, has been widely used in treating digestive diseases and ulcerative colitis for over a thousand years. In certain classical Tibetan Medicine, heavy metal may add as an active ingredient, but it may cause contamination unintentionally in some cases. Therefore, the toxicity and adverse effects of TTM became to draw public attention. In this study, 48 male Wistar rats were orally administrated with different dosages of RMP once a day for 15 consecutive days, then half of the rats were euthanized on the 15th day and the remaining were euthanized on the 30th day. Plasma, kidney and liver samples were acquired to 1H NMR metabolomics analysis. Histopathology and ICP-MS were applied to support the metabolomics findings. The metabolic signature of plasma from RMP-administrated rats exhibited increasing levels of glucose, betaine, and creatine, together with decreasing levels of lipids, 3-hydroxybutate, pyruvate, citrate, valine, leucine, isoleucine, glutamate, and glutamine. The metabolomics analysis results of liver showed that after RMP administration, the concentrations of valine, leucine, proline, tyrosine, and tryptophan elevated, while glucose, sarcosine and 3-hydroxybutyrate decreased. The levels of metabolites in kidney, such as, leucine, valine, isoleucine and tyrosine, were increased, while taurine, glutamate, and glutamine decreased. The study provides several potential biomarkers for the toxicity mechanism research of RMP and shows that RMP may cause injury in kidney and liver and disturbance of several pathways, such as energy metabolism, oxidative stress, glucose and amino acids metabolism.

  19. LC-MS based Metabolomics

    DEFF Research Database (Denmark)

    Magdenoska, Olivera

    metabolites with liquid chromatography mass spectrometry (LC-MS) as the most commonly used. The primary goal of this Ph.D. study was to develop an LC-MS method together with sample preparation for analysis of intracellular metabolites such as nucleotides, sugar phosphates, organic acids, coenzymes etc...... during this Ph.D. study were successfully applied for targeted and multitargeted analysis of different classes of intracellular metabolites such as nucleotides, sugar phosphates, coeznymes and organic acids. In addition sample preparation methods were established for different microorganisms capable...... recovery of the metabolites after the extraction. Quenching and extraction procedures for bacteria, yeast, mammalian cells and filamentous fungi were tested. Cold MeOH as a quenching method combined with boiling EtOH or MeOH/chloroform as extraction method showed to work well for Saccharomyces cerevisiae...

  20. Biological variation of Vanilla planifolia leaf metabolome.

    Science.gov (United States)

    Palama, Tony Lionel; Fock, Isabelle; Choi, Young Hae; Verpoorte, Robert; Kodja, Hippolyte

    2010-04-01

    The metabolomic analysis of Vanilla planifolia leaves collected at different developmental stages was carried out using (1)H-nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis in order to evaluate their variation. Ontogenic changes of the metabolome were considered since leaves of different ages were collected at two different times of the day and in two different seasons. Principal component analysis (PCA) and partial least square modeling discriminate analysis (PLS-DA) of (1)H NMR data provided a clear separation according to leaf age, time of the day and season of collection. Young leaves were found to have higher levels of glucose, bis[4-(beta-D-glucopyranosyloxy)-benzyl]-2-isopropyltartrate (glucoside A) and bis[4-(beta-D-glucopyranosyloxy)-benzyl]-2-(2-butyl)-tartrate (glucoside B), whereas older leaves had more sucrose, acetic acid, homocitric acid and malic acid. Results obtained from PLS-DA analysis showed that leaves collected in March 2008 had higher levels of glucosides A and B as compared to those collected in August 2007. However, the relative standard deviation (RSD) exhibited by the individual values of glucosides A and B showed that those compounds vary more according to their developmental stage (50%) than to the time of day or the season in which they were collected (19%). Although morphological variations of the V. planifolia accessions were observed, no clear separation of the accessions was determined from the analysis of the NMR spectra. The results obtained in this study, show that this method based on the use of (1)H NMR spectroscopy in combination with multivariate analysis has a great potential for further applications in the study of vanilla leaf metabolome. Copyright 2009 Elsevier Ltd. All rights reserved.

  1. Serum Metabolomics of Burkitt Lymphoma Mouse Models.

    Directory of Open Access Journals (Sweden)

    Fengmin Yang

    Full Text Available Burkitt lymphoma (BL is a rare and highly aggressive type of non-Hodgkin lymphoma. The mortality rate of BL patients is very high due to the rapid growth rate and frequent systemic spread of the disease. A better understanding of the pathogenesis, more sensitive diagnostic tools and effective treatment methods for BL are essential. Metabolomics, an important aspect of systems biology, allows the comprehensive analysis of global, dynamic and endogenous biological metabolites based on their nuclear magnetic resonance (NMR and mass spectrometry (MS. It has already been used to investigate the pathogenesis and discover new biomarkers for disease diagnosis and prognosis. In this study, we analyzed differences of serum metabolites in BL mice and normal mice by NMR-based metabolomics. We found that metabolites associated with energy metabolism, amino acid metabolism, fatty acid metabolism and choline phospholipid metabolism were altered in BL mice. The diagnostic potential of the metabolite differences was investigated in this study. Glutamate, glycerol and choline had a high diagnostic accuracy; in contrast, isoleucine, leucine, pyruvate, lysine, α-ketoglutarate, betaine, glycine, creatine, serine, lactate, tyrosine, phenylalanine, histidine and formate enabled the accurate differentiation of BL mice from normal mice. The discovery of abnormal metabolism and relevant differential metabolites may provide useful clues for developing novel, noninvasive approaches for the diagnosis and prognosis of BL based on these potential biomarkers.

  2. In-plant reliability data base for nuclear power plant components: data collection and methodology report

    International Nuclear Information System (INIS)

    Drago, J.P.; Borkowski, R.J.; Pike, D.H.; Goldberg, F.F.

    1982-07-01

    The development of a component reliability data for use in nuclear power plant probabilistic risk assessments and reliabiilty studies is presented in this report. The sources of the data are the in-plant maintenance work request records from a sample of nuclear power plants. This data base is called the In-Plant Reliability Data (IPRD) system. Features of the IPRD system are compared with other data sources such as the Licensee Event Report system, the Nuclear Plant Reliability Data system, and IEEE Standard 500. Generic descriptions of nuclear power plant systems formulated for IPRD are given

  3. Using NMR-Based Metabolomics to Evaluate Postprandial Urinary Responses Following Consumption of Minimally Processed Wheat Bran or Wheat Aleurone by Men and Women.

    Science.gov (United States)

    Garg, Ramandeep; Brennan, Lorraine; Price, Ruth K; Wallace, Julie M W; Strain, J J; Gibney, Mike J; Shewry, Peter R; Ward, Jane L; Garg, Lalit; Welch, Robert W

    2016-02-17

    Wheat bran, and especially wheat aleurone fraction, are concentrated sources of a wide range of components which may contribute to the health benefits associated with higher consumption of whole-grain foods. This study used NMR metabolomics to evaluate urine samples from baseline at one and two hours postprandially, following the consumption of minimally processed bran, aleurone or control by 14 participants (7 Females; 7 Males) in a randomized crossover trial. The methodology discriminated between the urinary responses of control, and bran and aleurone, but not between the two fractions. Compared to control, consumption of aleurone or bran led to significantly and substantially higher urinary concentrations of lactate, alanine, N-acetylaspartate acid and N-acetylaspartylglutamate and significantly and substantially lower urinary betaine concentrations at one and two hours postprandially. There were sex related differences in urinary metabolite profiles with generally higher hippurate and citrate and lower betaine in females compared to males. Overall, this postprandial study suggests that acute consumption of bran or aleurone is associated with a number of physiological effects that may impact on energy metabolism and which are consistent with longer term human and animal metabolomic studies that used whole-grain wheat diets or wheat fractions.

  4. Investigation of the Antifatigue Effects of Korean Ginseng on Professional Athletes by Gas Chromatography-Time-of-Flight-Mass Spectrometry-Based Metabolomics.

    Science.gov (United States)

    Yan, Bei; Liu, Yao; Shi, Aixin; Wang, Zhihong; Aa, Jiye; Huang, Xiaoping; Liu, Yi

    2017-09-19

    Ginseng is usually used for alleviating fatigue. The purpose of this paper was to evaluate the regulatory effect of Korean ginseng on the metabolic pattern in professional athletes, and, further, to explore the underlying mechanism of the antifatigue effect of Korean ginseng. GC-time-of-flight-MS was used to profile serum samples from professional athletes before training and after 15 and 30 day training, and professional athletes administered with Korean ginseng in the meanwhile. Biochemical parameters of all athletes were also analyzed. For the athlete control group, strength–endurance training resulted in an elevation of creatine kinase (CK) and blood urea nitrogen (BUN), and a reduction in blood hemoglobin, and a dynamic trajectory of the metabolomic profile which were related to fatigue. Korean ginseng treatment not only lead to a marked reduction in CK and blood urea nitrogen (BUN) in serum, but also showed regulatory effects on the serum metabolic profile and restored scores plots close to normal, suggesting that the change in metabolic profiling could reflect the antifatigue effect of Korean ginseng. Furthermore, perturbed levels of 11 endogenous metabolites were regulated by Korean ginseng significantly, which might be primarily involved in lipid metabolism, energy balance, and chemical signaling. These findings suggest that metabolomics is a potential tool for the evaluation of the antifatigue effect of Korean ginseng and for the elucidation of its pharmacological mechanism.

  5. Metabolomics strategy for the mapping of volatile exometabolome from Saccharomyces spp. widely used in the food industry based on comprehensive two-dimensional gas chromatography.

    Science.gov (United States)

    Martins, Cátia; Brandão, Tiago; Almeida, Adelaide; Rocha, Sílvia M

    2017-05-01

    Saccharomyces spp. are widely used in the food and beverages industries. Their cellular excreted metabolites are important for general quality of products and can contribute to product differentiation. This exploratory study presents a metabolomics strategy for the comprehensive mapping of cellular metabolites of two yeast species, Saccharomyces cerevisiae and S. pastorianus (both collected in an industrial context) through a multidimensional chromatography platform. Solid-phase microextraction was used as a sample preparation method. The yeast viability, a specific technological quality parameter, was also assessed. This untargeted analysis allowed the putative identification of 525 analytes, distributed over 14 chemical families, the origin of which may be explained through the pathways network associated with yeasts metabolism. The expression of the different metabolic pathways was similar for both species, event that seems to be yeast genus dependent. Nevertheless, these species showed different growth rates, which led to statistically different metabolites content. This was the first in-depth approach that characterizes the headspace content of S. cerevisiae and S. pastorianus species cultures. The combination of a sample preparation method capable of providing released volatile metabolites directly from yeast culture headspace with comprehensive two-dimensional gas chromatography was successful in uncovering a specific metabolomic pattern for each species. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  6. Analyses of tropistic responses using metabolomics.

    Science.gov (United States)

    Millar, Katherine D L; Kiss, John Z

    2013-01-01

    Characterization of phototropism and gravitropism has been through gene expression studies, assessment of curvature response, and protein expression experiments. To our knowledge, the current study is the first to determine how the metabolome, the complete set of small-molecule metabolites within a plant, is impacted during these tropisms. We have determined the metabolic profile of plants during gravitropism and phototropism. Seedlings of Arabidopsis thaliana wild type (WT) and phyB mutant were exposed to unidirectional light (red or blue) or reoriented to induce a tropistic response, and small-molecule metabolites were assayed and quantified. A subset of the WT was analyzed using microarray experiments to obtain gene profiling data. Analyses of the metabolomic data using principal component analysis showed a common profile in the WT during the different tropistic curvatures, but phyB mutants produced a distinctive profile for each tropism. Interestingly, the gravity treatment elicited the greatest changes in gene expression of the WT, followed by blue light, then by red light treatments. For all tropisms, we identified genes that were downregulated by a large magnitude in carbohydrate metabolism and secondary metabolism. These included ATCSLA15, CELLULOSE SYNTHASE-LIKE, and ATCHS/SHS/TT4, CHALCONE SYNTHASE. In addition, genes involved in amino acid biosynthesis were strongly upregulated, and these included THA1 (THREONINE ALDOLASE 1) and ASN1 (DARK INDUCIBLE asparagine synthase). We have established the first metabolic profile of tropisms in conjunction with transcriptomic analyses. This approach has been useful in characterizing the similarities and differences in the molecular mechanisms involved with phototropism and gravitropism.

  7. Metabox: A Toolbox for Metabolomic Data Analysis, Interpretation and Integrative Exploration.

    Science.gov (United States)

    Wanichthanarak, Kwanjeera; Fan, Sili; Grapov, Dmitry; Barupal, Dinesh Kumar; Fiehn, Oliver

    2017-01-01

    Similar to genomic and proteomic platforms, metabolomic data acquisition and analysis is becoming a routine approach for investigating biological systems. However, computational approaches for metabolomic data analysis and integration are still maturing. Metabox is a bioinformatics toolbox for deep phenotyping analytics that combines data processing, statistical analysis, functional analysis and integrative exploration of metabolomic data within proteomic and transcriptomic contexts. With the number of options provided in each analysis module, it also supports data analysis of other 'omic' families. The toolbox is an R-based web application, and it is freely available at http://kwanjeeraw.github.io/metabox/ under the GPL-3 license.

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

    Energy Technology Data Exchange (ETDEWEB)

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

    2008-03-31

    The goal of metabolomics experiments is the detection and quantitation of as many sample components as reasonably possible in order to identify “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 imperative that metabolome sample constituents be efficiently separated prior to ion production, in order to minimize the phenomenon of ionization suppression. Similarly, optimization of the MS inlet can lead to increased measurement sensitivity. This 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.

  9. Editorial: from plant biotechnology to bio-based products.

    Science.gov (United States)

    Stöger, Eva

    2013-10-01

    From plant biotechnology to bio-based products - this Special Issue of Biotechnology Journal is dedicated to plant biotechnology and is edited by Prof. Eva Stöger (University of Natural Resources and Life Sciences, Vienna, Austria). The Special Issue covers a wide range of topics in plant biotechnology, including metabolic engineering of biosynthesis pathways in plants; taking advantage of the scalability of the plant system for the production of innovative materials; as well as the regulatory challenges and society acceptance of plant biotechnology. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

  10. Metabolomics and detection of colorectal cancer in humans: a systematic review.

    Science.gov (United States)

    Wang, Haili; Tso, Victor K; Slupsky, Carolyn M; Fedorak, Richard N

    2010-09-01

    Metabolomics represents one of the new omics sciences and capitalizes on the unique presence and concentration of small molecules in tissues and body fluids to construct a 'fingerprint' that can be unique to the individual and, within that individual, unique to environmental influences, including health and disease states. As such, metabolomics has the potential to serve an important role in diagnosis and management of human conditions. Colorectal cancer is a major public health concern. Current population-based screening methods are suboptimal and whether metabolomics could represent a new tool of screening is under investigation. The purpose of this systematic review is to summarize existing literature on metabolomics and colorectal cancer, in terms of diagnostic accuracies and distinguishing metabolites. Eight studies are included. A total of 12 metabolites (taurine, lactate, choline, inositol, glycine, phosphocholine, proline, phenylalanine, alanine, threonine, valine and leucine) were found to be more prevalent in colorectal cancer and glucose was found to be in higher proportion in control specimens using tissue metabolomics. Serum and urine metabolomics identified several other differential metabolites between controls and colorectal cancer patients. This article highlights the novelty of the field of metabolomics in colorectal oncology.

  11. YMDB: the Yeast Metabolome Database

    Science.gov (United States)

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

    2012-01-01

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

  12. An integrated RNAseq-1H NMR metabolomics approach to understand soybean primary metabolism regulation in response to Rhizoctonia foliar blight disease.

    Science.gov (United States)

    Copley, Tanya R; Aliferis, Konstantinos A; Kliebenstein, Daniel J; Jabaji, Suha H

    2017-04-27

    Rhizoctonia solani AG1-IA is a devastating phytopathogen causing Rhizoctonia foliar blight (RFB) of soybean worldwide with yield losses reaching 60%. Plant defense mechanisms are complex and information from different metabolic pathways is required to thoroughly understand plant defense regulation and function. Combining information from different "omics" levels such as transcriptomics, metabolomics, and proteomics is required to gain insights into plant metabolism and its regulation. As such, we studied fluctuations in soybean metabolism in response to R. solani infection at early and late disease stages using an integrated transcriptomics-metabolomics approach, focusing on the regulation of soybean primary metabolism and oxidative stress tolerance. Transcriptomics (RNAseq) and metabolomics ( 1 H NMR) data were analyzed individually and by integration using bidirectional orthogonal projections to latent structures (O2PLS) to reveal possible links between the metabolome and transcriptome during early and late infection stages. O2PLS analysis detected 516 significant transcripts, double that reported in the univariate analysis, and more significant metabolites than detected in partial least squares discriminant analysis. Strong separation of treatments based on integration of the metabolomes and transcriptomes of the analyzed soybean leaves was revealed, similar trends as those seen in analyses done on individual datasets, validating the integration method being applied. Strong fluctuations of soybean primary metabolism occurred in glycolysis, the TCA cycle, photosynthesis and photosynthates in response to R. solani infection. Data were validated using quantitative real-time PCR on a set of specific markers as well as randomly selected genes. Significant increases in transcript and metabolite levels involved in redox reactions and ROS signaling, such as peroxidases, thiamine, tocopherol, proline, L-alanine and GABA were also recorded. Levels of ethanol increased 24

  13. Metabolomic Modularity Analysis (MMA) to Quantify Human Liver Perfusion Dynamics.

    Science.gov (United States)

    Sridharan, Gautham Vivek; Bruinsma, Bote; Bale, Shyam Sundhar; Swaminathan, Anandh; Saeidi, Nima; Yarmush, Martin L; Uygun, Korkut

    2017-11-13

    Large-scale -omics data are now ubiquitously utilized to capture and interpret global responses to perturbations in biological systems, such as the impact of disease states on cells, tissues, and whole organs. Metabolomics data, in particular, are difficult to interpret for providing physiological insight because predefined biochemical pathways used for analysis are inherently biased and fail to capture more complex network interactions that span multiple canonical pathways. In this study, we introduce a nov-el approach coined Metabolomic Modularity Analysis (MMA) as a graph-based algorithm to systematically identify metabolic modules of reactions enriched with metabolites flagged to be statistically significant. A defining feature of the algorithm is its ability to determine modularity that highlights interactions between reactions mediated by the production and consumption of cofactors and other hub metabolites. As a case study, we evaluated the metabolic dynamics of discarded human livers using time-course metabolomics data and MMA to identify modules that explain the observed physiological changes leading to liver recovery during subnormothermic machine perfusion (SNMP). MMA was performed on a large scale liver-specific human metabolic network that was weighted based on metabolomics data and identified cofactor-mediated modules that would not have been discovered by traditional metabolic pathway analyses.

  14. Non-target effects of GM potato: an eco-metabolomics approach

    OpenAIRE

    Plischke, Andreas

    2013-01-01

    In this thesis, patterns of variation in plant metabolomes and insect communities were described in GM and non-GM potato plants in both laboratory and field experiments. Differences between plant genotypes in insect abundances were small when compared to year-to-year differences, location effects and differences between developmental stages of plants. Standardized effect sizes are discussed as an alternative scale for measuring effects. Leaf age, aphid infestation and virus infection were fou...

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

    Science.gov (United States)

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

    2015-11-01

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

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

    Science.gov (United States)

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

    2015-01-01

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

  17. Radiation Metabolomics: Current Status and Future Directions

    Directory of Open Access Journals (Sweden)

    Smrithi eSugumaran Menon

    2016-02-01

    Full Text Available Human exposure to ionizing radiation disrupts normal metabolic processes in cells and organs by inducing complex biological responses that interfere with gene and protein expression. Conventional dosimetry, monitoring of prodromal symptoms and peripheral lymphocyte counts are of limited value as organ and tissue specific biomarkers for personnel exposed to radiation, particularly, weeks or months after exposure. Analysis of metabolites generated in known stress-responsive pathways by molecular profiling helps to predict the physiological status of an individual in response to environmental or genetic perturbations. Thus, a multi-metabolite profile obtained from a high resolution mass spectrometry-based metabolomics platform offers potential for identification of robust biomarkers to predict radiation toxicity of organs and tissues resulting from exposures to therapeutic or non-therapeutic ionizing radiation. Here, we review the status of radiation metabolomics and explore applications as a standalone technology, as well as its integration in systems biology, to facilitate a better understanding of the molecular basis of radiation response. Finally, we draw attention to the identification of specific pathways that can be targeted for the development of therapeutics to alleviate or mitigate harmful effects of radiation exposure.

  18. Metabolomics Application in Maternal-Fetal Medicine

    OpenAIRE

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

    2013-01-01

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

  19. Long-chain unsaturated fatty acids as possible important metabolites for primary angle-closure glaucoma based on targeted metabolomic analysis.

    Science.gov (United States)

    Rong, Shengzhong; Li, Yang; Guan, Yue; Zhu, Lili; Zhou, Qiang; Gao, Mucong; Pan, Hongzhi; Zou, Lina; Chang, Dong

    2017-09-01

    Primary angle-closure glaucoma (PACG) is a severe chronic neurodegenerative disease in Asia. Identification of important metabolites associated with PACG is crucial for early intervention and advancing knowledge of the disease mechanism. We applied gas chromatography-mass spectrometry (GC-MS) for targeted metabolomic analysis on serum samples from 38 newly diagnosed PACG patients and 48 controls. Palmitoleic acid (PA), linoleic acid (LA), γ-linolenic acid (GLA) and arachidonic acid (ARA) were identified as important metabolites associated with PACG. PA and GLA were significantly elevated (p fatty acid metabolic profiles between PACG patients and control subjects. Furthermore, PA, LA, ARA and GLA appear to have clinical applications for the screening of PACG. Copyright © 2017 John Wiley & Sons, Ltd.

  20. Metabolomics-driven nutraceutical evaluation of diverse green tea cultivars.

    Directory of Open Access Journals (Sweden)

    Yoshinori Fujimura

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

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

    Science.gov (United States)

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

    2011-01-01

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

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

    Directory of Open Access Journals (Sweden)

    Masakazu eShinohara

    2012-04-01

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

  3. Metabolomics in Toxicology and Preclinical Research

    Science.gov (United States)

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

    2013-01-01

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

  4. Untargeted metabolomic analysis in naturally occurring canine diabetes mellitus identifies similarities to human Type 1 Diabetes

    OpenAIRE

    O?Kell, Allison L.; Garrett, Timothy J.; Wasserfall, Clive; Atkinson, Mark A.

    2017-01-01

    While predominant as a disease entity, knowledge voids exist regarding the pathogenesis of canine diabetes. To test the hypothesis that diabetic dogs have similar metabolomic perturbations to humans with type 1 diabetes (T1D), we analyzed serum metabolomic profiles of breed- and body weight-matched, diabetic (n?=?6) and healthy (n?=?6) dogs by liquid chromatography-mass spectrometry (LC-MS) profiling. We report distinct clustering of diabetic and control groups based on heat map analysis of k...

  5. Metabolomics techniques for nanotoxicity investigations.

    Science.gov (United States)

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

    2015-01-01

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

  6. Metabolomics and bioactive substances in plants

    DEFF Research Database (Denmark)

    Khakimov, Bekzod

    (Analytical and Bioanalytical Chemistry, In Press, DOI: 10.1007/s00216-013-7341-z) outlines a novel GC-MS derivatization method using TMSCN for trimethylsilylation for improved analysis of complex biological mixtures . A review paper (Journal of Cereal Science, Accepted) written for the special issue...

  7. The research for the design verification of nuclear power plant based on VR dynamic plant

    International Nuclear Information System (INIS)

    Wang Yong; Yu Xiao

    2015-01-01

    This paper studies a new method of design verification through the VR plant, in order to perform verification and validation the design of plant conform to the requirements of accident emergency. The VR dynamic plant is established by 3D design model and digital maps that composed of GIS system and indoor maps, and driven by the analyze data of design analyzer. The VR plant could present the operation conditions and accident conditions of power plant. This paper simulates the execution of accident procedures, the development of accidents, the evacuation planning of people and so on, based on VR dynamic plant, and ensure that the plant design will not cause bad effect. Besides design verification, simulated result also can be used for optimization of the accident emergency plan, the training of accident plan and emergency accident treatment. (author)

  8. Metabolomics and ischaemic heart disease.

    Science.gov (United States)

    Rasmiena, Aliki A; Ng, Theodore W; Meikle, Peter J

    2013-03-01

    Ischaemic heart disease accounts for nearly half of the global cardiovascular disease burden. Aetiologies relating to heart disease are complex, but dyslipidaemia, oxidative stress and inflammation are cardinal features. Despite preventative measures and advancements in treatment regimens with lipid-lowering agents, the high prevalence of heart disease and the residual risk of recurrent events continue to be a significant burden to the health sector and to the affected individuals and their families. The development of improved risk models for the early detection and prevention of cardiovascular events in addition to new therapeutic strategies to address this residual risk are required if we are to continue to make inroads into this most prevalent of diseases. Metabolomics and lipidomics are modern disciplines that characterize the metabolite and lipid complement respectively, of a given system. Their application to ischaemic heart disease has demonstrated utilities in population profiling, identification of multivariate biomarkers and in monitoring of therapeutic response, as well as in basic mechanistic studies. Although advances in magnetic resonance and mass spectrometry technologies have given rise to the fields of metabolomics and lipidomics, the plethora of data generated presents challenges requiring specific statistical and bioinformatics applications, together with appropriate study designs. Nonetheless, the predictive and re-classification capacity of individuals with various degrees of risk by the plasma lipidome has recently been demonstrated. In the present review, we summarize evidence derived exclusively by metabolomic and lipidomic studies in the context of ischaemic heart disease. We consider the potential role of plasma lipid profiling in assessing heart disease risk and therapeutic responses, and explore the potential mechanisms. Finally, we highlight where metabolomic studies together with complementary -omic disciplines may make further

  9. Ethnobotanical perspective of antimalarial plants: traditional knowledge based study.

    Science.gov (United States)

    Qayum, Abdul; Arya, Rakesh; Lynn, Andrew M

    2016-02-04

    Considering the demand of antimalarial plants it has become essential to find and locate them for their optimal extraction. The work aims to find plants with antimalarial activities which were used by the local people; to raise the value of traditional knowledge system (TKS) prevalent in the study region; to compile characteristics of local plants used in malaria treatment (referred as antimalarial plants) and to have its spatial distribution analysis to establish a concept of geographical health. Antimalarial plants are listed based on literature survey and field data collected during rainy season, from 85 respondents comprised of different ethnic groups. Ethno-medicinal utilities of plants was extracted; botanical name, family, local name, part used, folklore, geographical location and image of plants were recorded after cross validating with existing literatures. The interview was trifurcated in field, Vaidya/Hakims and house to house. Graphical analysis was done for major plants families, plant part used, response of people and patients and folklore. Mathematical analysis was done for interviewee's response, methods of plant identification and people's preferences of TKS through three plant indices. Fifty-one plants belonging to 27 families were reported with its geographical attributes. It is found plant root (31.75 %) is used mostly for malaria treatment and administration mode is decoction (41.2 %) mainly. The study area has dominance of plants of family Fabaceae (7), Asteraceae (4), Acanthaceae (4) and Amaranthaceae (4). Most popular plants found are Adhatoda vasica, Cassia fistula and Swertia chirata while  % usage of TKS is 82.0 % for malaria cure. The research findings can be used by both scientific community and common rural people for bio-discovery of these natural resources sustainably. The former can extract the tables to obtain a suitable plant towards finding a suitable lead molecule in a drug discovery project; while the latter can meet their

  10. Structure Elucidation of Unknown Metabolites in Metabolomics by Combined NMR and MS/MS Prediction.

    Science.gov (United States)

    Boiteau, Rene M; Hoyt, David W; Nicora, Carrie D; Kinmonth-Schultz, Hannah A; Ward, Joy K; Bingol, Kerem

    2018-01-17

    We introduce a cheminformatics approach that combines highly selective and orthogonal structure elucidation parameters; accurate mass, MS/MS (MS²), and NMR into a single analysis platform to accurately identify unknown metabolites in untargeted studies. The approach starts with an unknown LC-MS feature, and then combines the experimental MS/MS and NMR information of the unknown to effectively filter out the false positive candidate structures based on their predicted MS/MS and NMR spectra. We demonstrate the approach on a model mixture, and then we identify an uncatalogued secondary metabolite in Arabidopsis thaliana . The NMR/MS² approach is well suited to the discovery of new metabolites in plant extracts, microbes, soils, dissolved organic matter, food extracts, biofuels, and biomedical samples, facilitating the identification of metabolites that are not present in experimental NMR and MS metabolomics databases.

  11. Statistical analysis of proteomics, metabolomics, and lipidomics data using mass spectrometry

    CERN Document Server

    Mertens, Bart

    2017-01-01

    This book presents an overview of computational and statistical design and analysis of mass spectrometry-based proteomics, metabolomics, and lipidomics data. This contributed volume provides an introduction to the special aspects of statistical design and analysis with mass spectrometry data for the new omic sciences. The text discusses common aspects of design and analysis between and across all (or most) forms of mass spectrometry, while also providing special examples of application with the most common forms of mass spectrometry. Also covered are applications of computational mass spectrometry not only in clinical study but also in the interpretation of omics data in plant biology studies. Omics research fields are expected to revolutionize biomolecular research by the ability to simultaneously profile many compounds within either patient blood, urine, tissue, or other biological samples. Mass spectrometry is one of the key analytical techniques used in these new omic sciences. Liquid chromatography mass ...

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

    Directory of Open Access Journals (Sweden)

    Bavaresco Luigi

    2017-01-01

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

  13. Gas Chromatography/Mass Spectrometry-Based Metabolomic Profiling Reveals Alterations in Mouse Plasma and Liver in Response to Fava Beans.

    Science.gov (United States)

    Xiao, Man; Du, Guankui; Zhong, Guobing; Yan, Dongjing; Zeng, Huazong; Cai, Wangwei

    2016-01-01

    Favism is a life-threatening hemolytic anemia resulting from the intake of fava beans by susceptible individuals with low erythrocytic glucose 6-phosphate dehydrogenase (G6PD) activity. However, little is known about the metabolomic changes in plasma and liver after the intake of fava beans in G6PD normal and deficient states. In this study, gas chromatography/mass spectrometry was used to analyze the plasma and liver metabolic alterations underlying the effects of fava beans in C3H- and G6PD-deficient (G6PDx) mice, and to find potential biomarkers and metabolic changes associated with favism. Our results showed that fava beans induced oxidative stress in both C3H and G6PDx mice. Significantly, metabolomic differences were observed in plasma and liver between the control and fava bean treated groups of both C3H and G6PDx mice. The levels of 7 and 21 metabolites in plasma showed significant differences between C3H-control (C3H-C)- and C3H fava beans-treated (C3H-FB) mice, and G6PDx-control (G6PDx-C)- and G6PDx fava beans-treated (G6PDx-FB) mice, respectively. Similarly, the levels of 7 and 25 metabolites in the liver showed significant differences between C3H and C3H-FB, and G6PDx and G6PDx-FB, respectively. The levels of oleic acid, linoleic acid, and creatinine were significantly increased in the plasma of both C3H-FB and G6PDx-FB mice. In the liver, more metabolic alterations were observed in G6PDx-FB mice than in C3H-FB mice, and were involved in a sugar, fatty acids, amino acids, cholesterol biosynthesis, the urea cycle, and the nucleotide metabolic pathway. These findings suggest that oleic acid, linoleic acid, and creatinine may be potential biomarkers of the response to fava beans in C3H and G6PDx mice and therefore that oleic acid and linoleic acid may be involved in oxidative stress induced by fava beans. This study demonstrates that G6PD activity in mice can affect their metabolic pathways in response to fava beans.

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

    NARCIS (Netherlands)

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

    2005-01-01

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

  15. Possible Future SOFC - ST Based Power Plants

    DEFF Research Database (Denmark)

    Rokni, Masoud; Scappin, Fabio

    2009-01-01

    Hybrid systems consisting Solid Oxide Fuel Cell (SOFC) on the top of a Steam Turbine (ST) are investigated. The plants are fired by natural gas. A desulfurization reactor removes the sulfur content in the NG while a pre-reformer break down the heavier hydrocarbons. The pre-treated fuel enters the...... is considerably more than the conventional combined cycles (CC). Both ASR (Adiabatic Steam Reformer) and CPO (Catalytic Partial Oxidation) fuel reformer reactors are considered in this study.......Hybrid systems consisting Solid Oxide Fuel Cell (SOFC) on the top of a Steam Turbine (ST) are investigated. The plants are fired by natural gas. A desulfurization reactor removes the sulfur content in the NG while a pre-reformer break down the heavier hydrocarbons. The pre-treated fuel enters...

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

    Directory of Open Access Journals (Sweden)

    Cseke Leland J

    2011-05-01

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

  17. A Metabolomic Perspective on Coeliac Disease

    Science.gov (United States)

    Calabrò, Antonio

    2014-01-01

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

  18. submitter Metabolomic Profile of Low–Copy Number Carriers at the Salivary α-Amylase Gene Suggests a Metabolic Shift Toward Lipid-Based Energy Production

    CERN Document Server

    Arredouani, Abdelilah; Culeddu, Nicola; Moustafa, Julia El-Sayed; Tichet, Jean; Balkau, Beverley; Brousseau, Thierry; Manca, Marco; Falchi, Mario

    2016-01-01

    Low serum salivary amylase levels have been associated with a range of metabolic abnormalities, including obesity and insulin resistance. We recently suggested that a low copy number at the AMY1 gene, associated with lower enzyme levels, also increases susceptibility to obesity. To advance our understanding of the effect of AMY1 copy number variation on metabolism, we compared the metabolomic signatures of high– and low–copy number carriers. We analyzed, using mass spectrometry and nuclear magnetic resonance (NMR), the sera of healthy normal-weight women carrying either low–AMY1 copies (LAs: four or fewer copies; n = 50) or high–AMY1 copies (HAs: eight or more copies; n = 50). Best-fitting multivariate models (empirical P < 1 × $10^{−3})$ of mass spectrometry and NMR data were concordant in showing differences in lipid metabolism between the two groups. In particular, LA carriers showed lower levels of long- and medium-chain fatty acids, and higher levels of dicarboxylic fatty acids and 2-hydrox...

  19. Selection of candidate radiation bio-markers in the serum of rats exposed to gamma-rays by GC/TOFMS-based metabolomics

    International Nuclear Information System (INIS)

    Liu, H.; Wang, Z.; Zhang, X.; Qiao, Y.; Wu, S.; Dong, F.; Chen, Y.

    2013-01-01

    In the study, gas chromatography/time-of-flight mass spectrometry (GC/TOFMS) techniques coupled with principal components analysis (PCA) were used to investigate metabolite perturbations in the serum of the rats exposed to 0.75, 3 or 8 Gy gamma rays. Male standard deviation rats were gamma-irradiated at doses of 0.75, 3 and 8 Gy (1.9 Gy min -1 ) or sham-irradiated. Serum samples were collected over the first 24 h under the exposure to irradiation in order to analyse the samples by GC/TOFMS. And multivariate data were analysed by PCA. The composition of metabolites in serum yielded distinct metabolomic phenotypes for 0.75, 3 and 8 Gy at 24 h after irradiation. Nine serum metabolites were significantly altered as a result of radiation exposure. Up-regulated metabolites included inositol, serine, lysine, glycine, threonine and glycerol; down regulated metabolites included isocitrate, gluconic acid and stearic acid. The nine metabolites were significantly altered after ionising radiation for they may be the potential bio-markers for the diagnosis of radiation injury. All rights reserved. (authors)

  20. Mass Spectrometry Based Metabolomics Comparison of Liver Grafts from Donors after Circulatory Death (DCD and Donors after Brain Death (DBD Used in Human Orthotopic Liver Transplantation.

    Directory of Open Access Journals (Sweden)

    Olga Hrydziuszko

    Full Text Available Use of marginal liver grafts, especially those from donors after circulatory death (DCD, has been considered as a solution to organ shortage. Inferior outcomes have been attributed to donor warm ischaemic damage in these DCD organs. Here we sought to profile the metabolic mechanisms underpinning donor warm ischaemia. Non-targeted Fourier transform ion cyclotron resonance (FT-ICR mass spectrometry metabolomics was applied to biopsies of liver grafts from donors after brain death (DBD; n = 27 and DCD (n = 10, both during static cold storage (T1 as well as post-reperfusion (T2. Furthermore 6 biopsies from DBD donors prior to the organ donation (T0 were also profiled. Considering DBD and DCD together, significant metabolic differences were discovered between T1 and T2 (688 peaks that were primarily related to amino acid metabolism, meanwhile T0 biopsies grouped together with T2, denoting the distinctively different metabolic activity of the perfused state. Major metabolic differences were discovered between DCD and DBD during cold-phase (T1 primarily related to glucose, tryptophan and kynurenine metabolism, and in the post-reperfusion phase (T2 related to amino acid and glutathione metabolism. We propose tryptophan/kynurenine and S-adenosylmethionine as possible biomarkers for the previously established higher graft failure of DCD livers, and conclude that the associated pathways should be targeted in more exhaustive and quantitative investigations.

  1. 1H NMR spectroscopy-based metabolomics analysis for the diagnosis of symptomatic E. coli-associated urinary tract infection (UTI).

    Science.gov (United States)

    Lussu, Milena; Camboni, Tania; Piras, Cristina; Serra, Corrado; Del Carratore, Francesco; Griffin, Julian; Atzori, Luigi; Manzin, Aldo

    2017-09-21

    Urinary tract infection (UTI) is one of the most common diagnoses in girls and women, and to a lesser extent in boys and men younger than 50 years. Escherichia coli, followed by Klebsiella spp. and Proteus spp., cause 75-90% of all infections. Infection of the urinary tract is identified by growth of a significant number of a single species in the urine, in the presence of symptoms. Urinary culture is an accurate diagnostic method but takes several hours or days to be carried out. Metabolomics analysis aims to identify biomarkers that are capable of speeding up diagnosis. Urine samples from 51 patients with a prior diagnosis of Escherichia coli-associated UTI, from 21 patients with UTI caused by other pathogens (bacteria and fungi), and from 61 healthy controls were analyzed. The 1 H-NMR spectra were acquired and processed. Multivariate statistical models were applied and their performance was validated using permutation test and ROC curve. Orthogonal Partial Least Squares-discriminant Analysis (OPLS-DA) showed good separation (R 2 Y = 0.76, Q2=0.45, p infections to test their specificity. Acetate and trimethylamine were identified as optimal candidates for biomarkers for UTI diagnosis. The conclusions support the possibility of a fast diagnostic test for Escherichia coli-associated UTI using acetate and trimethylamine concentrations.

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

    Science.gov (United States)

    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.

  3. NMR and pattern recognition methods in metabolomics: From data acquisition to biomarker discovery: A review

    International Nuclear Information System (INIS)

    Smolinska, Agnieszka; Blanchet, Lionel; Buydens, Lutgarde M.C.; Wijmenga, Sybren S.

    2012-01-01

    Highlights: ► Procedures for acquisition of different biofluids by NMR. ► Recent developments in metabolic profiling of different biofluids by NMR are presented. ► The crucial steps involved in data preprocessing and multivariate chemometric analysis are reviewed. ► Emphasis is given on recent findings on Multiple Sclerosis via NMR and pattern recognition methods. - Abstract: Metabolomics is the discipline where endogenous and exogenous metabolites are assessed, identified and quantified in different biological samples. Metabolites are crucial components of biological system and highly informative about its functional state, due to their closeness to functional endpoints and to the organism's phenotypes. Nuclear Magnetic Resonance (NMR) spectroscopy, next to Mass Spectrometry (MS), is one of the main metabolomics analytical platforms. The technological developments in the field of NMR spectroscopy have enabled the identification and quantitative measurement of the many metabolites in a single sample of biofluids in a non-targeted and non-destructive manner. Combination of NMR spectra of biofluids and pattern recognition methods has driven forward the application of metabolomics in the field of biomarker discovery. The importance of metabolomics in diagnostics, e.g. in identifying biomarkers or defining pathological status, has been growing exponentially as evidenced by the number of published papers. In this review, we describe the developments in data acquisition and multivariate analysis of NMR-based metabolomics data, with particular emphasis on the metabolomics of Cerebrospinal Fluid (CSF) and biomarker discovery in Multiple Sclerosis (MScl).

  4. Plasma metabolomics for the diagnosis and prognosis of H1N1 influenza pneumonia.

    Science.gov (United States)

    Banoei, Mohammad M; Vogel, Hans J; Weljie, Aalim M; Kumar, Anand; Yende, Sachin; Angus, Derek C; Winston, Brent W

    2017-04-19

    Metabolomics is a tool that has been used for the diagnosis and prognosis of specific diseases. The purpose of this study was to examine if metabolomics could be used as a potential diagnostic and prognostic tool for H1N1 pneumonia. Our hypothesis was that metabolomics can potentially be used early for the diagnosis and prognosis of H1N1 influenza pneumonia. 1 H nuclear magnetic resonance spectroscopy and gas chromatography-mass spectrometry were used to profile the metabolome in 42 patients with H1N1 pneumonia, 31 ventilated control subjects in the intensive care unit (ICU), and 30 culture-positive plasma samples from patients with bacterial community-acquired pneumonia drawn within the first 24 h of hospital admission for diagnosis and prognosis of disease. We found that plasma-based metabolomics from samples taken within 24 h of hospital admission can be used to discriminate H1N1 pneumonia from bacterial pneumonia and nonsurvivors from survivors of H1N1 pneumonia. Moreover, metabolomics is a highly sensitive and specific tool for the 90-day prognosis of mortality in H1N1 pneumonia. This study demonstrates that H1N1 pneumonia can create a quite different plasma metabolic profile from bacterial culture-positive pneumonia and ventilated control subjects in the ICU on the basis of plasma samples taken within 24 h of hospital/ICU admission, early in the course of disease.

  5. Untargeted metabolomic analysis of tomato pollen development and heat stress response

    NARCIS (Netherlands)

    Paupière, Marine J.; Müller, Florian; Li, Hanjing; Rieu, Ivo; Tikunov, Yury M.; Visser, Richard G.F.; Bovy, Arnaud G.

    2017-01-01

    Key message: Pollen development metabolomics.Abstract: Developing pollen is among the plant structures most sensitive to high temperatures, and a decrease in pollen viability is often associated with an alteration of metabolite content. Most of the metabolic studies of pollen have focused on a

  6. Perplexing Metabolomes in Fungal-Insect Trophic Interactions: A Terra Incognita of Mycobiocontrol Mechanisms

    Science.gov (United States)

    Singh, Digar; Son, Su Y.; Lee, Choong H.

    2016-01-01

    The trophic interactions of entomopathogenic fungi in different ecological niches viz., soil, plants, or insect themselves are effectively regulated by their maneuvered metabolomes and the plethora of metabotypes. In this article, we discuss a holistic framework of co-evolutionary metabolomes and metabotypes to model the interactions of biocontrol fungi especially with mycosed insects. Conventionally, the studies involving fungal biocontrol mechanisms are reported in the context of much aggrandized fungal entomotoxins while the adaptive response mechanisms of host insects are relatively overlooked. The present review asserts that the selective pressure exerted among the competing or interacting species drives alterations in their overall metabolomes which ultimately implicates in corresponding metabotypes. Quintessentially, metabolomics offers a most generic and tractable model to assess the fungal-insect antagonism in terms of interaction biomarkers, biosynthetic pathway plasticity, and their co-evolutionary defense. The fungi chiefly rely on a battery of entomotoxins viz., secondary metabolites falling in the categories of NRP’s (non-ribosomal peptides), PK’s (polyketides), lysine derive alkaloids, and terpenoids. On the contrary, insects overcome mycosis through employing different layers of immunity manifested as altered metabotypes (phenoloxidase activity) and overall metabolomes viz., carbohydrates, lipids, fatty acids, amino acids, and eicosanoids. Here, we discuss the recent findings within conventional premise of fungal entomotoxicity and the evolution of truculent immune response among host insect. The metabolomic frameworks for fungal–insect interaction can potentially transmogrify our current comprehensions of biocontrol mechanisms to develop the hypervirulent biocontrol strains with least environmental concerns. Moreover, the interaction metabolomics (interactome) in complementation with other -omics cascades could further be applied to address

  7. Supporting plant operation through computer-based procedures

    International Nuclear Information System (INIS)

    Martinez, Victor; Medrano, Javier; Mendez, Julio

    2014-01-01

    Digital Systems are becoming more important in controlling and monitoring nuclear power plant operations. The capabilities of these systems provide additional functions as well as support operators in making decisions and avoiding errors. Regarding Operation Support Systems, an important way of taking advantage of these features is using computer-based procedures (CBPs) tools that enhance the plant operation. Integrating digital systems in analogue controls at nuclear power plants in operation becomes an extra challenge, in contrast to the integration of Digital Control Systems in new nuclear power plants. Considering the potential advantages of using this technology, Tecnatom has designed and developed a CBP platform taking currently operating nuclear power plants as its design basis. The result is a powerful tool which combines the advantages of CBPs and the conventional analogue control systems minimizing negative effects during plant operation and integrating operation aid-systems to support operators. (authors)

  8. Functional Analysis of Metabolomics Data.

    Science.gov (United States)

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

    2016-01-01

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

  9. Use of Rhizosphere Metabolomics to Investigate Exudation of Phenolics by Arabidopsis Roots

    Science.gov (United States)

    Lee, Yong Jian; Rai, Amit; Reuben, Sheela; Nesati, Victor; Almeida, Reinaldo; Swarup, Sanjay

    2013-04-01

    and anthocyanin metabolites. We describe here the metabolites present in the root exudates using high resolution accurate mass (HRAM) metabolomics approach. Using this approach, biased rhizosphere for another class of PGPR strains can now be created. In this case, lignin- and anthocyanin- utilizing strains will be selectively preferred. We have set up a platform to perform metabolomics of exudates at the root surface. This has allowed us to use the liquid extraction surface analysis (LESA) system using a Thermo Velos Pro Orbitrap-MS to identify differences in exudate profiles along the root system of Arabidopsis. This platform enables direct sampling and measurement from plant roots grown aeroponically. As the metabolites are extracted from root surface and directly injected into the mass spectrometer, there is minimal loss of sample in this process. This method will now allow us to further dissect rhizosphere properties from places such as young root apex, as well as from the more mature base of roots. Taken together, these resources of altered rhizosphere, nutrient utilization pathways in microbes and surface analysis technology will help in extending our understanding of the processes in the plant rhizosphere.

  10. Mass spectrometry data of metabolomics analysis of Nepenthes pitchers.

    Science.gov (United States)

    Rosli, Muhammad Aqil Fitri; Azizan, Kamalrul Azlan; Baharum, Syarul Nataqain; Goh, Hoe-Han

    2017-10-01

    Hybridisation plays a significant role in the evolution and diversification of plants. Hybridisation among Nepenthes species is extensive, either naturally or man-made. To investigate the effects of hybridisation on the chemical compositions, we carried out metabolomics study on pitcher tissue of Nepenthes ampullaria, Nepenthes rafflesiana and their hybrid, Nepenthes × hookeriana . Pitcher samples were harvested and extracted in methanol:chloroform:water via sonication-assisted extraction before analysed using LC-TOF-MS. MS data were analysed using XCMS online version 2.2.5. This is the first MS data report towards the profiling, identification and comprehensive comparison of metabolites present in Nepenthes species.

  11. Mass spectrometry data of metabolomics analysis of Nepenthes pitchers

    Directory of Open Access Journals (Sweden)

    Muhammad Aqil Fitri Rosli

    2017-10-01

    Full Text Available Hybridisation plays a significant role in the evolution and diversification of plants. Hybridisation among Nepenthes species is extensive, either naturally or man-made. To investigate the effects of hybridisation on the chemical compositions, we carried out metabolomics study on pitcher tissue of Nepenthes ampullaria, Nepenthes rafflesiana and their hybrid, Nepenthes × hookeriana. Pitcher samples were harvested and extracted in methanol:chloroform:water via sonication-assisted extraction before analysed using LC-TOF-MS. MS data were analysed using XCMS online version 2.2.5. This is the first MS data report towards the profiling, identification and comprehensive comparison of metabolites present in Nepenthes species.

  12. Development of uniformly stable isotope labeling system in higher plants for hetero-nuclear NMR experiments in vitro and in vivo

    International Nuclear Information System (INIS)

    Kikuchi, J.

    2005-01-01

    Full text: Novel methods for measurement of living systems are making new breakthroughs in life science. In the era of the metabolome (analysis of all measurable metabolites), a MS-based approach is considered to be the major technology, whereas a NMR-based method is recognized as minor technology due to its low sensitivity. Therefore, my laboratory is currently focusing to develop novel methodologies for an NMR-based metabolomics. This will be achieved by uniform stable isotope labeling of higher plants allowing application of multi-dimensional NMR experiments used in protein structure determination. Using these novel methods, I will analyze the dynamic molecular networks inside tissues. Especially, use of stable isotope labeling methods has enormous advantage for discrimination of incorporated or de novo synthesized compounds. Furthermore, potentiality of in vivo-NMR metabolomics will be discussed in the conference. (author)

  13. Amino Acid and Biogenic Amine Profile Deviations in an Oral Glucose Tolerance Test: A Comparison between Healthy and Hyperlipidaemia Individuals Based on Targeted Metabolomics

    Directory of Open Access Journals (Sweden)

    Qi Li

    2016-06-01

    Full Text Available Hyperlipidemia (HLP is characterized by a disturbance in lipid metabolism and is a primary risk factor for the development of insulin resistance (IR and a well-established risk factor for cardiovascular disease and atherosclerosis. The aim of this work was to investigate the changes in postprandial amino acid and biogenic amine profiles provoked by an oral glucose tolerance test (OGTT in HLP patients using targeted metabolomics. We used ultra-high-performance liquid chromatography-triple quadrupole mass spectrometry to analyze the serum amino acid and biogenic amine profiles of 35 control and 35 HLP subjects during an OGTT. The amino acid and biogenic amine profiles from 30 HLP subjects were detected as independent samples to validate the changes in the metabolites. There were differences in the amino acid and biogenic amine profiles between the HLP individuals and the healthy controls at baseline and after the OGTT. The per cent changes of 13 metabolites from fasting to the 2 h samples during the OGTT in the HLP patients were significantly different from those of the healthy controls. The lipid parameters were associated with the changes in valine, isoleucine, creatine, creatinine, dimethylglycine, asparagine, serine, and tyrosine (all p < 0.05 during the OGTT in the HLP group. The postprandial changes in isoleucine and γ-aminobutyric acid (GABA during the OGTT were positively associated with the homeostasis model assessment of insulin resistance (HOMA-IR; all p < 0.05 in the HLP group. Elevated oxidative stress and disordered energy metabolism during OGTTs are important characteristics of metabolic perturbations in HLP. Our findings offer new insights into the complex physiological regulation of metabolism during the OGTT in HLP.

  14. Sparse Mbplsr for Metabolomics Data and Biomarker Discovery

    DEFF Research Database (Denmark)

    Karaman, İbrahim

    2014-01-01

    Metabolomics is part of systems biology and a rapidly evolving field. It is a tool to analyze multiple metabolic changes in biofluids and tissues and aims at determining biomarkers in the metabolism. LC-MS (liquid chromatography – mass spectrometry), GC-MS (gas chromatography – mass spectrometry...... the link between high throughput metabolomics data generated on different analytical platforms, discover important metabolites deriving from the digestion processes in the gut, and automate metabolic pathway discovery from mass spectrometry. PLS (partial least squares) based chemometric methods were......, potential biomarkers from LC-MS and NMR data could be detected and the relationships among the measurement variables of both analytical methods could be studied. Detection of potential biomarkers is followed up by an identification process through online metabolite and pathway databases. This process...

  15. Fusarium oxysporum mediates systems metabolic reprogramming of chickpea roots as revealed by a combination of proteomics and metabolomics.

    Science.gov (United States)

    Kumar, Yashwant; Zhang, Limin; Panigrahi, Priyabrata; Dholakia, Bhushan B; Dewangan, Veena; Chavan, Sachin G; Kunjir, Shrikant M; Wu, Xiangyu; Li, Ning; Rajmohanan, Pattuparambil R; Kadoo, Narendra Y; Giri, Ashok P; Tang, Huiru; Gupta, Vidya S

    2016-07-01

    Molecular changes elicited by plants in response to fungal attack and how this affects plant-pathogen interaction, including susceptibility or resistance, remain elusive. We studied the dynamics in root metabolism during compatible and incompatible interactions between chickpea and Fusarium oxysporum f. sp. ciceri (Foc), using quantitative label-free proteomics and NMR-based metabolomics. Results demonstrated differential expression of proteins and metabolites upon Foc inoculations in the resistant plants compared with the susceptible ones. Additionally, expression analysis of candidate genes supported the proteomic and metabolic variations in the chickpea roots upon Foc inoculation. In particular, we found that the resistant plants revealed significant increase in the carbon and nitrogen metabolism; generation of reactive oxygen species (ROS), lignification and phytoalexins. The levels of some of the pathogenesis-related proteins were significantly higher upon Foc inoculation in the resistant plant. Interestingly, results also exhibited the crucial role of altered Yang cycle, which contributed in different methylation reactions and unfolded protein response in the chickpea roots against Foc. Overall, the observed modulations in the metabolic flux as outcome of several orchestrated molecular events are determinant of plant's role in chickpea-Foc interactions. © 2016 The Authors. Plant Biotechnology Journal published by Society for Experimental Biology and The Association of Applied Biologists and John Wiley & Sons Ltd.

  16. The role of metabolomics in neonatal and pediatric laboratory medicine.

    Science.gov (United States)

    Mussap, Michele; Antonucci, Roberto; Noto, Antonio; Fanos, Vassilios

    2013-11-15

    Metabolomics consists of the quantitative analysis of a large number of low molecular mass metabolites involving substrates or products in metabolic pathways existing in all living systems. The analysis of the metabolic profile detectable in a human biological fluid allows to instantly identify changes in the composition of endogenous and exogenous metabolites caused by the interaction between specific physiopathological states, gene expression, and environment. In pediatrics and neonatology, metabolomics offers new encouraging perspectives for the improvement of critically ill patient outcome, for the early recognition of metabolic profiles associated with the development of diseases in the adult life, and for delivery of individualized medicine. In this view, nutrimetabolomics, based on the recognition of specific cluster of metabolites associated with nutrition and pharmacometabolomics, based on the capacity to personalize drug therapy by analyzing metabolic modifications due to therapeutic treatment may open new frontiers in the prevention and in the treatment of pediatric and neonatal diseases. This review summarizes the most relevant results published in the literature on the application of metabolomics in pediatric and neonatal clinical settings. However, there is the urgent need to standardize physiological and preanalytical variables, analytical methods, data processing, and result presentation, before establishing the definitive clinical value of results. © 2013 Elsevier B.V. All rights reserved.

  17. Knowledge based diagnostics in nuclear power plants

    International Nuclear Information System (INIS)

    Baldeweg, F.; Fiedler, U.; Weiss, F.P.; Werner, M.

    1987-01-01

    In this paper a special process diagnostic system (PDS) is presented. It must be seen as the result of a long term work on computerized process surveillance and control; it includes a model based system for noise analysis of mechanical vibrations, which has recently been enhanced by using of knowledge based technique (expert systems). The paper discusses the process diagnostic frame concept and emphasize the vibration analysis expert system

  18. Image-based phenotyping of plant disease symptoms

    Directory of Open Access Journals (Sweden)

    Andrew eMutka

    2015-01-01

    Full Text Available Plant diseases cause significant reductions in agricultural productivity worldwide. Disease symptoms have deleterious effects on the growth and development of crop plants, limiting yields and making agricultural products unfit for consumption. For many plant-pathogen systems, we lack knowledge of the physiological mechanisms that link pathogen infection and the production of disease symptoms in the host. A variety of quantitative high-throughput image-based methods for phenotyping plant growth and development are currently being developed. These methods range from detailed analysis of a single plant over time to broad assessment of the crop canopy for thousands of plants in a field and employ a wide variety of imaging technologies. Application of these methods to the study of plant disease offers the ability to study quantitatively how host physiology is altered by pathogen infection. These approaches have the potential to provide insight into the physiological mechanisms underlying disease symptom development. Furthermore, imaging techniques that detect the electromagnetic spectrum outside of visible light allow us to quantify disease symptoms that are not visible by eye, increasing the range of symptoms we can observe and potentially allowing for earlier and more thorough symptom detection. In this review, we summarize current progress in plant disease phenotyping and suggest future directions that will accelerate the development of resistant crop varieties.

  19. Image-based phenotyping of plant disease symptoms.

    Science.gov (United States)

    Mutka, Andrew M; Bart, Rebecca S

    2014-01-01

    Plant diseases cause significant reductions in agricultural productivity worldwide. Disease symptoms have deleterious effects on the growth and development of crop plants, limiting yields and making agricultural products unfit for consumption. For many plant-pathogen systems, we lack knowledge of the physiological mechanisms that link pathogen infection and the production of disease symptoms in the host. A variety of quantitative high-throughput image-based methods for phenotyping plant growth and development are currently being developed. These methods range from detailed analysis of a single plant over time to broad assessment of the crop canopy for thousands of plants in a field and employ a wide variety of imaging technologies. Application of these methods to the study of plant disease offers the ability to study quantitatively how host physiology is altered by pathogen infection. These approaches have the potential to provide insight into the physiological mechanisms underlying disease symptom development. Furthermore, imaging techniques that detect the electromagnetic spectrum outside of visible light allow us to quantify disease symptoms that are not visible by eye, increasing the range of symptoms we can observe and potentially allowing for earlier and more thorough symptom detection. In this review, we summarize current progress in plant disease phenotyping and suggest future directions that will accelerate the development of resistant crop varieties.

  20. Knowledge bases for modelisation of industrial plants

    International Nuclear Information System (INIS)

    Lorre, J.P.; Evrard, J.M.; Dorlet, E.

    1992-01-01

    Our experience in the development of numerous knowledge based control systems for large industrial applications has led us to the expression of a generic problem and to the implementation of the tools to address it. This paper illustrates, with different practical examples that we have encountered, the principal concepts found in the modelling and management of large industrial knowledge bases. We thus arrive at the definition of the formalism to be used. The principles described are now integrated into the tool SPIRAL and are currently being employed in the development of several applications

  1. Surface feature based classification of plant organs from 3D laserscanned point clouds for plant phenotyping.

    Science.gov (United States)

    Paulus, Stefan; Dupuis, Jan; Mahlein, Anne-Katrin; Kuhlmann, Heiner

    2013-07-27

    Laserscanning recently has become a powerful and common method for plant parameterization and plant growth observation on nearly every scale range. However, 3D measurements with high accuracy, spatial resolution and speed result in a multitude of points that require processing and analysis. The primary objective of this research has been to establish a reliable and fast technique for high throughput phenotyping using differentiation, segmentation and classification of single plants by a fully automated system. In this report, we introduce a technique for automated classification of point clouds of plants and present the applicability for plant parameterization. A surface feature histogram based approach from the field of robotics was adapted to close-up laserscans of plants. Local geometric point features describe class characteristics, which were used to distinguish among different plant organs. This approach has been proven and tested on several plant species. Grapevine stems and leaves were classified with an accuracy of up to 98%. The proposed method was successfully transferred to 3D-laserscans of wheat plants for yield estimation. Wheat ears were separated with an accuracy of 96% from other plant organs. Subsequently, the ear volume was calculated and correlated to the ear weight, the kernel weights and the number of kernels. Furthermore the impact of the data resolution was evaluated considering point to point distances between 0.3 and 4.0 mm with respect to the classification accuracy. We introduced an approach using surface feature histograms for automated plant organ parameterization. Highly reliable classification results of about 96% for the separation of grapevine and wheat organs have been obtained. This approach was found to be independent of the point to point distance and applicable to multiple plant species. Its reliability, flexibility and its high order of automation make this method well suited for the demands of high throughput phenotyping.

  2. Toxicity of a plant based mosquito repellent/killer

    OpenAIRE

    Singh, Bhoopendra; Singh, Prakash Raj; Mohanty, Manoj Kumar

    2012-01-01

    The mission to make humans less attractive to mosquitoes has fuelled decades of scientific research on mosquito behaviour and control. The search for the perfect topical insect repellent/killer continues. This analysis was conducted to review and explore the scientific information on toxicity produced by the ingredients/contents of a herbal product. In this process of systemic review the following methodology was applied. By doing a MEDLINE search with key words of selected plants, plant base...

  3. Natural variation of root exudates in Arabidopsis thaliana-linking metabolomic and genomic data

    OpenAIRE

    Susann Mönchgesang; Nadine Strehmel; Stephan Schmidt; Lore Westphal; Franziska Taruttis; Erik Müller; Siska Herklotz; Steffen Neumann; Dierk Scheel

    2016-01-01

    Many metabolomics studies focus on aboveground parts of the plant, while metabolism within roots and the chemical composition of the rhizosphere, as influenced by exudation, are not deeply investigated. In this study, we analysed exudate metabolic patterns of Arabidopsis thaliana and their variation in genetically diverse accessions. For this project, we used the 19 parental accessions of the Arabidopsis MAGIC collection. Plants were grown in a hydroponic system, their exudates were harvested...

  4. Metabolomics study of the therapeutic mechanism of Schisandra Chinensis lignans in diet-induced hyperlipidemia mice.

    Science.gov (United States)

    Sun, Jing-Hui; Liu, Xu; Cong, Li-Xin; Li, He; Zhang, Cheng-Yi; Chen, Jian-Guang; Wang, Chun-Mei

    2017-08-01

    Schisandra, a globally distributed plant, has been widely applied for the treatment of diseases such as hyperlipidemia, fatty liver and obesity in China. In the present work, a rapid resolution liquid chromatography coupled with quadruple-time-of-flight mass spectrometry (RRLC-Q-TOF-MS)-based metabolomics was conducted to investigate the intervention effect of Schisandra chinensis lignans (SCL) on hyperlipidemia mice induced by high-fat diet (HFD). Hyperlipidemia mice were orally administered with SCL (100 mg/kg) once a day for 4 weeks. Serum biochemistry assay of triglyceride (TG), total cholesterol (TC), low-density lipoprotein cholesterol (LDL-c) and high-density lipoprotein cholesterol (HDL-c) was conducted to confirm the treatment of SCL on lipid regulation. Metabolomics analysis on serum samples was carried out, and principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were carried out for the pattern recognition and characteristic metabolites identification. The relative levels of critical regulatory factors of liver lipid metabolism, sterol regulatory element-binding proteins (SREBPs) and its related gene expressions were measured by quantitative real-time polymerase chain reaction (RT-PCR) for investigating the underlying mechanism. Oral administration of SCL significantly decreased the serum levels of TC, TG and LDL-c and increased the serum level of HDL-c in the hyperlipidemia mice, and no effect of SCL on blood lipid levels was observed in control mice. Serum samples were scattered in the PCA scores plots in response to the control, HFD and SCL group. Totally, thirteen biomarkers were identified and nine of them were recovered to the normal levels after SCL treatment. Based on the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways analysis, the anti-hyperlipidemia mechanisms of SCL may be involved in the following metabolic pathways: tricarboxylic acid (TCA) cycle, synthesis of ketone body and cholesterol

  5. Chemicalome and metabolome profiling of polymethoxylated flavonoids in Citri Reticulatae Pericarpium based on an integrated strategy combining background subtraction and modified mass defect filter in a Microsoft Excel Platform.

    Science.gov (United States)

    Zeng, Su-Ling; Duan, Li; Chen, Bai-Zhong; Li, Ping; Liu, E-Hu

    2017-07-28

    Detection of metabolites in complex biological matrixes is a great challenge because of the background noise and endogenous components. Herein, we proposed an integrated strategy that combined background subtraction program and modified mass defect filter (MMDF) data mining in a Microsoft Excel platform for chemicalome and metabolome profiling of the polymethoxylated flavonoids (PMFs) in Citri Reticulatae Pericarpium (CRP). The exogenously-sourced ions were firstly filtered out by the developed Visual Basic for Applications (VBA) program incorporated in the Microsoft Office. The novel MMDF strategy was proposed for detecting both target and untarget constituents and metabolites based on narrow, well-defined mass defect ranges. The approach was validated to be powerful, and potentially useful for the metabolite identification of both single compound and homologous compound mixture. We successfully identified 30 and 31 metabolites from rat biosamples after oral administration of nobiletin and tangeretin, respectively. A total of 56 PMFs compounds were chemically characterized and 125 metabolites were captured. This work demonstrated the feasibility of the integrated approach for reliable characterization of the constituents and metabolites in herbal medicines. Copyright © 2017 Elsevier B.V. All rights reserved.

  6. Investigation of the reverse effect of Danhong injection on doxorubicin-induced cardiotoxicity in H9c2 cells: Insight by LC-MS based non-targeted metabolomic analysis.

    Science.gov (United States)

    Yi, Xiaojiao; Zhu, Junfeng; Zhang, Jinghui; Gao, Yun; Chen, Zhongjian; Lu, Shihai; Cai, Zongwei; Hong, Yanjun; Wu, Yongjiang

    2018-04-15

    Although Danhong injection (DHI) has been clearly shown to attenuate ischemic myocardial injury and improve heart function, there is no research regarding its role in doxorubicin (DOX)-induced cardiomyopathy. In this study, we aimed to investigate the reverse effect of DHI on DOX-induced cardiotoxicity in H9c2 cells. The results of 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide (MTT) assay demonstrated that DHI had no cytotoxicity towards the relevant cell line unless the concentration was as high as 50 μL/mL. The satisfactory cardioprotective effect of DHI exerted at the concentration of 10 μL/mL, which agreed well with the result of real-time cell viability assay. Then non-targeted metabolomics based on LC-MS was employed to characterize metabolic alterations in DOX-induced cells with DHI treatment. Multivariate analysis, including PCA and PLS-DA, revealed 31 altered metabolites after DOX treatment that were primarily related to the disturbance of amino acids and nucleotides metabolism. While DHI could intervene in some disturbed metabolic pathways, such as the metabolism of arginine, glutathione (GSH), pantothenic acid, cytidine, inosine and 5'-methylthioadenosine. These results suggested that DHI exerted the therapeutic effect by improving energy metabolism and attenuating oxidative stress. The present study can lay a foundation for further research on the promising therapeutic effect of DHI in managing DOX-induced cardiotoxicity. Copyright © 2018 Elsevier B.V. All rights reserved.

  7. Effects of boiling duration in processing of White Paeony Root on its overall quality evaluated by ultra-high performance liquid chromatography quadrupole/time-of-flight mass spectrometry based metabolomics analysis and high performance liquid chromatography quantification.

    Science.gov (United States)

    Ming, Kong; Xu, Jun; Liu, Huan-Huan; Xu, Jin-Di; Li, Xiu-Yang; Lu, Min; Wang, Chun-Ru; Chen, Hu-Biao; Li, Song-Lin

    2017-01-01

    Boiling processing is commonly used in post-harvest handling of White Paeony Root (WPR), in order to whiten the herbal materials and preserve the bright color, since such WPR is empirically considered to possess a higher quality. The present study was designed to investigate whether and how the boiling processing affects overall quality of WPR. First, an ultra-high performance liquid chromatography quadrupole/time-of-flight mass spectrometry-based metabolomics approach coupled with multivariate statistical analysis was developed to compare the holistic quality of boiled and un-boiled WPR samples. Second, ten major components in WPR samples boiled for different durations were quantitatively determined using high performance liquid chromatography to further explore the effects of boiling time on the holistic quality of WPR, meanwhile the appearance of the processed herbal materials was observed. The results suggested that the boiling processing conspicuously affected the holistic quality of WPR by simultaneously and inconsistently altering the chemical compositions and that short-time boiling processing between 2 and 10 min could both make the WPR bright-colored and improve the contents of major bioactive components, which were not achieved either without boiling or with prolonged boiling. In conclusion, short-term boiling (2-10 min) is recommended for post-harvest handling of WPR. Copyright © 2017 China Pharmaceutical University. Published by Elsevier B.V. All rights reserved.

  8. Fault Diagnosis Strategies for SOFC-Based Power Generation Plants.

    Science.gov (United States)

    Costamagna, Paola; De Giorgi, Andrea; Gotelli, Alberto; Magistri, Loredana; Moser, Gabriele; Sciaccaluga, Emanuele; Trucco, Andrea

    2016-08-22

    The success of distributed power generation by plants based on solid oxide fuel cells (SOFCs) is hindered by reliability problems that can be mitigated through an effective fault detection and isolation (FDI) system. However, the numerous operating conditions under which such plants can operate and the random size of the possible faults make identifying damaged plant components starting from the physical variables measured in the plant very difficult. In this context, we assess two classical FDI strategies (model-based with fault signature matrix and data-driven with statistical classification) and the combination of them. For this assessment, a quantitative model of the SOFC-based plant, which is able to simulate regular and faulty conditions, is used. Moreover, a hybrid approach based on the random forest (RF) classification method is introduced to address the discrimination of regular and faulty situations due to its practical advantages. Working with a common dataset, the FDI performances obtained using the aforementioned strategies, with different sets of monitored variables, are observed and compared. We conclude that the hybrid FDI strategy, realized by combining a model-based scheme with a statistical classifier, outperforms the other strategies. In addition, the inclusion of two physical variables that should be measured inside the SOFCs can significantly improve the FDI performance, despite the actual difficulty in performing such measurements.

  9. Fault Diagnosis Strategies for SOFC-Based Power Generation Plants

    Science.gov (United States)

    Costamagna, Paola; De Giorgi, Andrea; Gotelli, Alberto; Magistri, Loredana; Moser, Gabriele; Sciaccaluga, Emanuele; Trucco, Andrea

    2016-01-01

    The success of distributed power generation by plants based on solid oxide fuel cells (SOFCs) is hindered by reliability problems that can be mitigated through an effective fault detection and isolation (FDI) system. However, the numerous operating conditions under which such plants can operate and the random size of the possible faults make identifying damaged plant components starting from the physical variables measured in the plant very difficult. In this context, we assess two classical FDI strategies (model-based with fault signature matrix and data-driven with statistical classification) and the combination of them. For this assessment, a quantitative model of the SOFC-based plant, which is able to simulate regular and faulty conditions, is used. Moreover, a hybrid approach based on the random forest (RF) classification method is introduced to address the discrimination of regular and faulty situations due to its practical advantages. Working with a common dataset, the FDI performances obtained using the aforementioned strategies, with different sets of monitored variables, are observed and compared. We conclude that the hybrid FDI strategy, realized by combining a model-based scheme with a statistical classifier, outperforms the other strategies. In addition, the inclusion of two physical variables that should be measured inside the SOFCs can significantly improve the FDI performance, despite the actual difficulty in performing such measurements. PMID:27556472

  10. Fault Diagnosis Strategies for SOFC-Based Power Generation Plants

    Directory of Open Access Journals (Sweden)

    Paola Costamagna

    2016-08-01

    Full Text Available The success of distributed power generation by plants based on solid oxide fuel cells (SOFCs is hindered by reliability problems that can be mitigated through an effective fault detection and isolation (FDI system. However, the numerous operating conditions under which such plants can operate and the random size of the possible faults make identifying damaged plant components starting from the physical variables measured in the plant very difficult. In this context, we assess two classical FDI strategies (model-based with fault signature matrix and data-driven with statistical classification and the combination of them. For this assessment, a quantitative model of the SOFC-based plant, which is able to simulate regular and faulty conditions, is used. Moreover, a hybrid approach based on the random forest (RF classification method is introduced to address the discrimination of regular and faulty situations due to its practical advantages. Working with a common dataset, the FDI performances obtained using the aforementioned strategies, with different sets of monitored variables, are observed and compared. We conclude that the hybrid FDI strategy, realized by combining a model-based scheme with a statistical classifier, outperforms the other strategies. In addition, the inclusion of two physical variables that should be measured inside the SOFCs can significantly improve the FDI performance, despite the actual difficulty in performing such measurements.

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

    Directory of Open Access Journals (Sweden)

    Joanna Hajduk

    2015-12-01

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

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

    Science.gov (United States)

    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. Biomarker discovery in neurological diseases: a metabolomic approach

    Directory of Open Access Journals (Sweden)

    Afaf El-Ansary

    2009-12-01

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

  14. Behavioral metabolomics analysis identifies novel neurochemical signatures in methamphetamine sensitization

    Science.gov (United States)

    Adkins, Daniel E.; McClay, Joseph L.; Vunck, Sarah A.; Batman, Angela M.; Vann, Robert E.; Clark, Shaunna L.; Souza, Renan P.; Crowley, James J.; Sullivan, Patrick F.; van den Oord, Edwin J.C.G.; Beardsley, Patrick M.

    2014-01-01

    Behavioral sensitization has been widely studied in animal models and is theorized to reflect neural modifications associated with human psychostimulant addiction. While the mesolimbic dopaminergic pathway is known to play a role, the neurochemical mechanisms underlying behavioral sensitization remain incompletely understood. In the present study, we conducted the first metabolomics analysis to globally characterize neurochemical differences associated with behavioral sensitization. Methamphetamine-induced sensitization measures were generated by statistically modeling longitudinal activity data for eight inbred strains of mice. Subsequent to behavioral testing, nontargeted liquid and gas chromatography-mass spectrometry profiling was performed on 48 brain samples, yielding 301 metabolite levels per sample after quality control. Association testing between metabolite levels and three primary dimensions of behavioral sensitization (total distance, stereotypy and margin time) showed four robust, significant associations at a stringent metabolome-wide significance threshold (false discovery rate < 0.05). Results implicated homocarnosine, a dipeptide of GABA and histidine, in total distance sensitization, GABA metabolite 4-guanidinobutanoate and pantothenate in stereotypy sensitization, and myo-inositol in margin time sensitization. Secondary analyses indicated that these associations were independent of concurrent methamphetamine levels and, with the exception of the myo-inositol association, suggest a mechanism whereby strain-based genetic variation produces specific baseline neurochemical differences that substantially influence the magnitude of MA-induced sensitization. These findings demonstrate the utility of mouse metabolomics for identifying novel biomarkers, and developing more comprehensive neurochemical models, of psychostimulant sensitization. PMID:24034544

  15. Metabolome of human gut microbiome is predictive of host dysbiosis

    Energy Technology Data Exchange (ETDEWEB)

    Larsen, Peter E.; Dai, Yang

    2015-09-14

    Background: Humans live in constant and vital symbiosis with a closely linked bacterial ecosystem called the microbiome, which influences many aspects of human health. When this microbial ecosystem becomes disrupted, the health of the human host can suffer; a condition called dysbiosis. However, the community compositions of human microbiomes also vary dramatically from individual to individual, and over time, making it difficult to uncover the underlying mechanisms linking the microbiome to human health. We propose that a microbiome’s interaction with its human host is not necessarily dependent upon the presence or absence of particular bacterial species, but instead is dependent on its community metabolome; an emergent property of the microbiome. Results: Using data from a previously published, longitudinal study of microbiome populations of the human gut, we extrapolated information about microbiome community enzyme profiles and metabolome models. Using machine learning techniques, we demonstrated that the aggregate predicted community enzyme function profiles and modeled metabolomes of a microbiome are more predictive of dysbiosis than either observed microbiome community composition or predicted enzyme function profiles. Conclusions: Specific enzyme functions and metabolites predictive of dysbiosis provide insights into the molecular mechanisms of microbiome–host interactions. The ability to use machine learning to predict dysbiosis from microbiome community interaction data provides a potentially powerful tool for understanding the links between the human microbiome and human health, pointing to potential microbiome-based diagnostics and therapeutic interventions.

  16. Metabolomics Application in Maternal-Fetal Medicine

    Directory of Open Access Journals (Sweden)

    Vassilios Fanos

    2013-01-01

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

  17. OPTIMAS-DW: A comprehensive transcriptomics, metabolomics, ionomics, proteomics and phenomics data resource for maize

    Directory of Open Access Journals (Sweden)

    Colmsee Christian

    2012-12-01

    Full Text Available Abstract Background Maize is a major crop plant, grown for human and animal nutrition, as well as a renewable resource for bioenergy. When looking at the problems of limited fossil fuels, the growth of the world’s population or the world’s climate change, it is important to find ways to increase the yield and biomass of maize and to study how it reacts to specific abiotic and biotic stress situations. Within the OPTIMAS systems biology project maize plants were grown under a large set of controlled stress conditions, phenotypically characterised and plant material was harvested to analyse the effect of specific environmental conditions or developmental stages. Transcriptomic, metabolomic, ionomic and proteomic parameters were measured from the same plant material allowing the comparison of results across different omics domains. A data warehouse was developed to store experimental data as well as analysis results of the performed experiments. Description The OPTIMAS Data Warehouse (OPTIMAS-DW is a comprehensive data collection for maize and integrates data from different data domains such as transcriptomics, metabolomics, ionomics, proteomics and phenomics. Within the OPTIMAS project, a 44K oligo chip was designed and annotated to describe the functions of the selected unigenes. Several treatment- and plant growth stage experiments were performed and measured data were filled into data templates and imported into the data warehouse by a Java based import tool. A web interface allows users to browse through all stored experiment data in OPTIMAS-DW including all data domains. Furthermore, the user can filter the data to extract information of particular interest. All data can be exported into different file formats for further data analysis and visualisation. The data analysis integrates data from different data domains and enables the user to find answers to different systems biology questions. Finally, maize specific pathway information is

  18. Remote sensing of plant trait responses to field-based plant-soil feedback using UAV-based optical sensors

    Science.gov (United States)

    van der Meij, Bob; Kooistra, Lammert; Suomalainen, Juha; Barel, Janna M.; De Deyn, Gerlinde B.

    2017-02-01

    Plant responses to biotic and abiotic legacies left in soil by preceding plants is known as plant-soil feedback (PSF). PSF is an important mechanism to explain plant community dynamics and plant performance in natural and agricultural systems. However, most PSF studies are short-term and small-scale due to practical constraints for field-scale quantification of PSF effects, yet field experiments are warranted to assess actual PSF effects under less controlled conditions. Here we used unmanned aerial vehicle (UAV)-based optical sensors to test whether PSF effects on plant traits can be quantified remotely. We established a randomized agro-ecological field experiment in which six different cover crop species and species combinations from three different plant families (Poaceae, Fabaceae, Brassicaceae) were grown. The feedback effects on plant traits were tested in oat (Avena sativa) by quantifying the cover crop legacy effects on key plant traits: height, fresh biomass, nitrogen content, and leaf chlorophyll content. Prior to destructive sampling, hyperspectral data were acquired and used for calibration and independent validation of regression models to retrieve plant traits from optical data. Subsequently, for each trait the model with highest precision and accuracy was selected. We used the hyperspectral analyses to predict the directly measured plant height (RMSE = 5.12 cm, R2 = 0.79), chlorophyll content (RMSE = 0.11 g m-2, R2 = 0.80), N-content (RMSE = 1.94 g m-2, R2 = 0.68), and fresh biomass (RMSE = 0.72 kg m-2, R2 = 0.56). Overall the PSF effects of the different cover crop treatments based on the remote sensing data matched the results based on in situ measurements. The average oat canopy was tallest and its leaf chlorophyll content highest in response to legacy of Vicia sativa monocultures (100 cm, 0.95 g m-2, respectively) and in mixture with Raphanus sativus (100 cm, 1.09 g m-2, respectively), while the lowest values (76 cm, 0.41 g m-2, respectively

  19. MicroRNA-based biotechnology for plant improvement.

    Science.gov (United States)

    Zhang, Baohong; Wang, Qinglian

    2015-01-01

    MicroRNAs (miRNAs) are an extensive class of newly discovered endogenous small RNAs, which negatively regulate gene expression at the post-transcription levels. As the application of next-generation deep sequencing and advanced bioinformatics, the miRNA-related study has been expended to non-model plant species and the number of identified miRNAs has dramatically increased in the past years. miRNAs play a critical role in almost all biological and metabolic processes, and provide a unique strategy for plant improvement. Here, we first briefly review the discovery, history, and biogenesis of miRNAs, then focus more on the application of miRNAs on plant breeding and the future directions. Increased plant biomass through controlling plant development and phase change has been one achievement for miRNA-based biotechnology; plant tolerance to abiotic and biotic stress was also significantly enhanced by regulating the expression of an individual miRNA. Both endogenous and artificial miRNAs may serve as important tools for plant improvement. © 2014 Wiley Periodicals, Inc.

  20. Structured Light-Based 3D Reconstruction System for Plants.

    Science.gov (United States)

    Nguyen, Thuy Tuong; Slaughter, David C; Max, Nelson; Maloof, Julin N; Sinha, Neelima

    2015-07-29

    Camera-based 3D reconstruction of physical objects is one of the most popular computer vision trends in recent years. Many systems have been built to model different real-world subjects, but there is lack of a completely robust system for plants. This paper presents a full 3D reconstruction system that incorporates both hardware structures (including the proposed structured light system to enhance textures on object surfaces) and software algorithms (including the proposed 3D point cloud registration and plant feature measurement). This paper demonstrates the ability to produce 3D models of whole plants created from multiple pairs of stereo images taken at different viewing angles, without the need to destructively cut away any parts of a plant. The ability to accurately predict phenotyping features, such as the number of leaves, plant height, leaf size and internode distances, is also demonstrated. Experimental results show that, for plants having a range of leaf sizes and a distance between leaves appropriate for the hardware design, the algorithms successfully predict phenotyping features in the target crops, with a recall of 0.97 and a precision of 0.89 for leaf detection and less than a 13-mm error for plant size, leaf size and internode distance.

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

    Science.gov (United States)

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

    2017-12-01

    readily be distinguished based on their source rock and the pH of the groundwater sample. Our results are promising regarding the future use of metabolomics techniques in this and other serpentinizing environments, for the identification of nutrients, biomarkers and metabolic pathways in the subsurface biosphere.

  2. Seismic force for base isolated nuclear power plants

    International Nuclear Information System (INIS)

    Yabana, Shuichi; Ishida, Katsuhiko

    1997-01-01

    In this report, dynamic and static seismic forces for base isolation system of nuclear power plants are described. First, concept of seismic force in guidelines of base isolated FBR plants, which was edited by CRIEPI in 'Verification Tests of FBR Seismic Isolation Systems' consigned from MITI, are mentioned. Second, proposed seismic spectrum is applied to ground motions in Hyogoken Nanbu Earthquake (1995). Assuming amplification factor of soil is 3, proposed seismic spectra agree with these ground motions as a result. Furthermore, calculation methods of static seismic force in which characteristics of seismic isolation systems are taken into account, are presented and the static force for Class A of nuclear power plants is compared with seismic force used in general base isolated buildings. (author)

  3. Feasibility design study. Land-based OTEC plants. Final report

    Energy Technology Data Exchange (ETDEWEB)

    Brewer, J. H.; Minor, J.; Jacobs, R.

    1979-01-01

    The purpose of this study has been to determine the feasibility of installing 10 MWe (MegaWatt-electric) and 40 MWe land-based OTEC demonstration power plants at two specific sites: Keahole Point on the western shore of the island of Hawaii; and Punta Tuna, on the southeast coast of the main island of Puerto Rico. In addition, the study has included development of design parameters, schedules and budgets for the design, construction and operation of these plants. Seawater systems (intake and discharge pipes) were to be sized so that flow losses were equivalent to those expected with a platform-based OTEC power plant. The power module (components and general arrangement was established based on the TRW design. Results are presented in detail. (WHK)

  4. Consumers' readiness to eat a plant-based diet.

    Science.gov (United States)

    Lea, E J; Crawford, D; Worsley, A

    2006-03-01

    The aim of this study was to examine consumers' readiness to change to a plant-based diet. Mail survey that included questions on readiness to change, eating habits and perceived benefits and barriers to the consumption of a plant-based diet. Victoria, Australia. A total of 415 randomly selected adults. In terms of their readiness to eat a plant-based diet, the majority (58%) of participants were in the precontemplation stage of change, while 14% were in contemplation/preparation, and 28% in action/maintenance. Those in the action/maintenance stage ate more fruit, vegetables, nuts, seeds, whole-meal bread, and cooked cereals than those in earlier stages. There were statistically significant differences in age and vegetarian status between the stages of change, but not for other demographic variables. There were strong differences across the stages of change with regard to perceived benefits and barriers to plant-based diets. For example, those in action/maintenance scored highest for benefit factors associated with well-being, weight, health, convenience and finances, whereas those in the precontemplation stage did not recognise such benefits. These findings can be utilised to help provide appropriate nutrition education and advertising, targeted at specific stages of change. For example, education about how it is possible to obtain iron and protein from a plant-based diet and on the benefits of change, in addition to tips on how to make a gradual, easy transition to a plant-based diet, could help progress precontemplators to later stages. Australian Research Council.

  5. Z Number Based Fuzzy Inference System for Dynamic Plant Control

    Directory of Open Access Journals (Sweden)

    Rahib H. Abiyev

    2016-01-01

    Full Text Available Frequently the reliabilities of the linguistic values of the variables in the rule base are becoming important in the modeling of fuzzy systems. Taking into consideration the reliability degree of the fuzzy values of variables of the rules the design of inference mechanism acquires importance. For this purpose, Z number based fuzzy rules that include constraint and reliability degrees of information are constructed. Fuzzy rule interpolation is presented for designing of an inference engine of fuzzy rule-based system. The mathematical background of the fuzzy inference system based on interpolative mechanism is developed. Based on interpolative inference process Z number based fuzzy controller for control of dynamic plant has been designed. The transient response characteristic of designed controller is compared with the transient response characteristic of the conventional fuzzy controller. The obtained comparative results demonstrate the suitability of designed system in control of dynamic plants.

  6. Photoprotection in Plants Optical Screening-based Mechanisms

    CERN Document Server

    Solovchenko, Alexei

    2010-01-01

    Optical screening of excessive and potentially harmful solar radiation is an important photoprotective mechanism, though it has received much less attention in comparison with other systems preventing photooxidative damage to photoautotrophic organisms. This photoprotection in the form of screening appears to be especially important for juvenile and senescing plants as well as under environmental stresses—i.e. in situations where the efficiency of enzymatic ROS elimination, DNA repair and other ‘classical’ photoprotective systems could be impaired. This book represents an attempt to develop an integral view of optical screening-based photoprotection in microalgae and higher plants. Towards this end, the key groups of pigments involved in the screening of ultraviolet and visible components of solar radiation in microalgae and higher plants, and the patterns of their accumulation and distribution within plant cells and tissues, are described. Special attention is paid to the manifestations of screening pi...

  7. Physics-Based Prognostics for Optimizing Plant Operation

    Energy Technology Data Exchange (ETDEWEB)

    Leonard J. Bond; Don B. Jarrell

    2005-03-01

    Scientists at the Pacific Northwest National Laboratory (PNNL) have examined the necessity for optimization of energy plant operation using 'DSOM{reg_sign}'--Decision Support Operation and Maintenance and this has been deployed at several sites. This approach has been expanded to include a prognostics components and tested on a pilot scale service water system, modeled on the design employed in a nuclear power plant. A key element in plant optimization is understanding and controlling the aging process of safety-specific nuclear plant components. This paper reports the development and demonstration of a physics-based approach to prognostic analysis that combines distributed computing, RF data links, the measurement of aging precursor metrics and their correlation with degradation rate and projected machine failure.

  8. AI-based alarm processing for a nuclear power plant

    International Nuclear Information System (INIS)

    Na, N.J.; Kim, I.S.; Hwang, I.K.; Lee, D.Y.; Ham, C.S.

    1996-01-01

    A real-time expert system is implemented using artificial intelligence and object-oriented technology for alarm processing and presentation in a nuclear power plant. The knowledge base is constructed based on some schemes to process and display alarms to the plant operators. The activated alarms are dynamically prioritized by the reasoning rules, and then, presented on the process mimic overview and by some other means. To demonstrate the proposed system, the alarm processing and presentation is carried out in a simulated environment of the TMI-2 accident

  9. Green systems biology - From single genomes, proteomes and metabolomes to ecosystems research and biotechnology.

    Science.gov (United States)

    Weckwerth, Wolfram

    2011-12-10

    biochemical networks up to whole species populations. This process relies on the development of new technologies for the analysis of molecular data, especially genomics, metabolomics and proteomics data. The ambitious aim of these non-targeted 'omic' technologies is to extend our understanding beyond the analysis of separated parts of the system, in contrast to traditional reductionistic hypothesis-driven approaches. The consequent integration of genotyping, pheno/morphotyping and the analysis of the molecular phenotype using metabolomics, proteomics and transcriptomics will reveal a novel understanding of plant metabolism and its interaction with the environment. The analysis of single model systems - plants, fungi, animals and bacteria - will finally emerge in the analysis of populations of plants and other organisms and their adaptation to the ecological niche. In parallel, this novel understanding of ecophysiology will translate into knowledge-based approaches in crop plant biotechnology and marker- or genome-assisted breeding approaches. In this review the foundations of green systems biology are described and applications in ecosystems research are presented. Knowledge exchange of ecosystems research and green biotechnology merging into green systems biology is anticipated based on the principles of natural variation, biodiversity and the genotype-phenotype environment relationship as the fundamental drivers of ecology and evolution. Copyright © 2011 Elsevier B.V. All rights reserved.

  10. Recent Development and Future Prospects of Plant-Based Vaccines.

    Science.gov (United States)

    Sohrab, Sayed Sartaj; Suhail, Mohd; Kamal, Mohammad A; Husen, Azamal; Azhar, Esam I

    2017-01-01

    Growing world population and continuous disease emergence have invited the development of more efficient new vaccines against a range of diseases. Conventional vaccines are being wildly used in the world but their production requires higher cost, more time and better infrastructure. Thus, the idea of plant-based edible vaccine technology has emerged and showed promising results with strong and effective protection against many diseases. Plants have been utilized since more than two decades as pharmaceuticals against many diseases. Plant-based technology has great potential to express genes and produce clinically important compounds in the desired tissue. Plant biotechnology has played important role in the production of pharmaceutical compounds like vaccines, antibodies, antigens, sub-units, growth hormones and enzymes by utilizing genetic modification. It has also been opened a new approach for developing an edible vaccine as an oral delivery. Edible vaccines have been shown to induce both mucosal as well as systemic immunity. Currently, many pharmaceuticals proteins as an edible vaccine have been developed in different plant expression systems and evaluated against various life-threatening diseases and some of them have reached advanced phase of the clinical trial and exhibited promising results. In this review, we have discussed about the molecular pharming, edible vaccines, plant base technology and current status of developed edible vaccines in the different plant tissue expression system, mechanism of action and clinical applications with clinical trials stage, significance, requirements, advantage and disadvantage of edible vaccines. Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.org.

  11. Evaluation of Four Different Analytical Tools to Determine the Regional Origin of Gastrodia elata and Rehmannia glutinosa on the Basis of Metabolomics Study

    Directory of Open Access Journals (Sweden)

    Dong-Kyu Lee

    2014-05-01

    Full Text Available Chemical profiles of medicinal plants could be dissimilar depending on the cultivation environments, which may influence their therapeutic efficacy. Accordingly, the regional origin of the medicinal plants should be authenticated for correct evaluation of their medicinal and market values. Metabolomics has been found very useful for discriminating the origin of many plants. Choosing the adequate analytical tool can be an essential procedure because different chemical profiles with different detection ranges will be produced according to the choice. In this study, four analytical tools, Fourier transform near‑infrared spectroscopy (FT-NIR, 1H-nuclear magnetic resonance spectroscopy (1H‑NMR, liquid chromatography-mass spectrometry (LC-MS, and gas chromatography-mass spectroscopy (GC-MS were applied in parallel to the same samples of two popular medicinal plants (Gastrodia elata and Rehmannia glutinosa cultivated either in Korea or China. The classification abilities of four discriminant models for each plant were evaluated based on the misclassification rate and Q2 obtained from principal component analysis (PCA and orthogonal projection to latent structures-discriminant analysis (OPLS‑DA, respectively. 1H-NMR and LC-MS, which were the best techniques for G. elata and R. glutinosa, respectively, were generally preferable for origin discrimination over the others. Reasoned by integrating all the results, 1H-NMR is the most prominent technique for discriminating the origins of two plants. Nonetheless, this study suggests that preliminary screening is essential to determine the most suitable analytical tool and statistical method, which will ensure the dependability of metabolomics-based discrimination.

  12. FIREDATA, Nuclear Power Plant Fire Event Data Base

    International Nuclear Information System (INIS)

    Wheelis, W.T.

    2001-01-01

    1 - Description of program or function: FIREDATA contains raw fire event data from 1965 through June 1985. These data were obtained from a number of reference sources including the American Nuclear Insurers, Licensee Event Reports, Nuclear Power Experience, Electric Power Research Institute Fire Loss Data and then collated into one database developed in the personal computer database management system, dBASE III. FIREDATA is menu-driven and asks interactive questions of the user that allow searching of the database for various aspects of a fire such as: location, mode of plant operation at the time of the fire, means of detection and suppression, dollar loss, etc. Other features include the capability of searching for single or multiple criteria (using Boolean 'and' or 'or' logical operations), user-defined keyword searches of fire event descriptions, summary displays of fire event data by plant name of calendar date, and options for calculating the years of operating experience for all commercial nuclear power plants from any user-specified date and the ability to display general plant information. 2 - Method of solution: The six database files used to store nuclear power plant fire event information, FIRE, DESC, SUM, OPEXPER, OPEXBWR, and EXPERPWR, are accessed by software to display information meeting user-specified criteria or to perform numerical calculations (e.g., to determine the operating experience of a nuclear plant). FIRE contains specific searchable data relating to each of 354 fire events. A keyword concept is used to search each of the 31 separate entries or fields. DESC contains written descriptions of each of the fire events. SUM holds basic plant information for all plants proposed, under construction, in operation, or decommissioned. This includes the initial criticality and commercial operation dates, the physical location of the plant, and its operating capacity. OPEXPER contains date information and data on how various plant locations are

  13. A review of plant-based compounds and medicinal plants effective on atherosclerosis

    Directory of Open Access Journals (Sweden)

    Mehrnoosh Sedighi

    2017-01-01

    Full Text Available Atherosclerosis is one of the most important cardiovascular diseases that involve vessels through the development of fatty streaks and plaques. Plant-based compounds can help treat or prevent atherosclerosis through affecting the involved factors. The main purpose of this review article is to investigate and introduce medicinal plants and their potential activities regarding antioxidant properties, effective on lipids level and development of plaque, atherosclerosis, and progression of atherosclerosis as well as the development of cardiovascular disease and ischemia. To search for the relevant articles indexed in Information Sciences Institute, PubMed, Scientific Information Database, IranMedex, and Scopus between 1980 and 2013, with further emphasis on those indexed from 2004 to 2015, we used these search terms: atherosclerosis, antioxidant, cholesterol, inflammation, and the medicinal plants below. Then, the articles with inclusion criteria were used in the final analysis of the findings. Plant-based active compounds, including phenols, flavonoids, and antioxidants, can be effective on atherosclerosis predisposing factors and hence in preventing this disease and associated harmful complications, especially through reducing cholesterol, preventing increase in free radicals, and ultimately decreasing vascular plaque and vascular resistance. Hence, medicinal plants can contribute to treating atherosclerosis and preventing its progression through reducing cholesterolemia, free radicals, inflammation, vascular resistance, and certain enzymes. They, alone or in combination with hypocholesterolemic drugs, can therefore be useful for patients with hyperlipidemia and its complications.

  14. A review of plant-based compounds and medicinal plants effective on atherosclerosis

    Science.gov (United States)

    Sedighi, Mehrnoosh; Bahmani, Mahmoud; Asgary, Sedigheh; Beyranvand, Fatemeh; Rafieian-Kopaei, Mahmoud

    2017-01-01

    Atherosclerosis is one of the most important cardiovascular diseases that involve vessels through the development of fatty streaks and plaques. Plant-based compounds can help treat or prevent atherosclerosis through affecting the involved factors. The main purpose of this review article is to investigate and introduce medicinal plants and their potential activities regarding antioxidant properties, effective on lipids level and development of plaque, atherosclerosis, and progression of atherosclerosis as well as the development of cardiovascular disease and ischemia. To search for the relevant articles indexed in Information Sciences Institute, PubMed, Scientific Information Database, IranMedex, and Scopus between 1980 and 2013, with further emphasis on those indexed from 2004 to 2015, we used these search terms: atherosclerosis, antioxidant, cholesterol, inflammation, and the medicinal plants below. Then, the articles with inclusion criteria were used in the final analysis of the findings. Plant-based active compounds, including phenols, flavonoids, and antioxidants, can be effective on atherosclerosis predisposing factors and hence in preventing this disease and associated harmful complications, especially through reducing cholesterol, preventing increase in free radicals, and ultimately decreasing vascular plaque and vascular resistance. Hence, medicinal plants can contribute to treating atherosclerosis and preventing its progression through reducing cholesterolemia, free radicals, inflammation, vascular resistance, and certain enzymes. They, alone or in combination with hypocholesterolemic drugs, can therefore be useful for patients with hyperlipidemia and its complications. PMID:28461816

  15. Local false discovery rate estimation using feature reliability in LC/MS metabolomics data.

    Science.gov (United States)

    Chong, Elizabeth Y; Huang, Yijian; Wu, Hao; Ghasemzadeh, Nima; Uppal, Karan; Quyyumi, Arshed A; Jones, Dean P; Yu, Tianwei

    2015-11-24

    False discovery rate (FDR) control is an important tool of statistical inference in feature selection. In mass spectrometry-based metabolomics data, features can be measured at different levels of reliability and false features are often detected in untargeted metabolite profiling as chemical and/or bioinformatics noise. The traditional false discovery rate methods treat all features equally, which can cause substantial loss of statistical power to detect differentially expressed features. We propose a reliability index for mass spectrometry-based metabolomics data with repeated measurements, which is quantified using a composite measure. We then present a new method to estimate the local false discovery rate (lfdr) that incorporates feature reliability. In simulations, our proposed method achieved better balance between sensitivity and controlling false discovery, as compared to traditional lfdr estimation. We applied our method to a real metabolomics dataset and were able to detect more differentially expressed metabolites that were biologically meaningful.

  16. Biomarkers for predicting type 2 diabetes development — Can metabolomics improve on existing biomarkers?

    DEFF Research Database (Denmark)

    Savolainen, Otto; Fagerberg, Björn; Lind, Mads Vendelbo

    2017-01-01

    Aim The aim was to determine if metabolomics could be used to build a predictive model for type 2 diabetes (T2D) risk that would improve prediction of T2D over current risk markers. Methods Gas chromatography-tandem mass spectrometry metabolomics was used in a nested case-control study based...... on a screening sample of 64-year-old Caucasian women (n = 629). Candidate metabolic markers of T2D were identified in plasma obtained at baseline and the power to predict diabetes was tested in 69 incident cases occurring during 5.5 years followup. The metabolomics results were used as a standalone prediction...... model and in combination with established T2D predictive biomarkers for building eight T2D prediction models that were compared with each other based on their sensitivity and selectivity for predicting T2D. Results Established markers of T2D (impaired fasting glucose, impaired glucose tolerance, insulin...

  17. Metabolomics Reveals Cryptic Interactive Effects of Species Interactions and Environmental Stress on Nitrogen and Sulfur Metabolism in Seagrass

    DEFF Research Database (Denmark)

    Hasler-Sheetal, Harald; Castorani, Max; Glud, Ronnie N.

    2016-01-01

    among foundational species and eventually affect ecosystem health. Here, we used metabolomics to assess the impact of light reductions on interactions between the seagrass Zostera marina, an important habitat-forming marine plant, and the abundant and commercially important blue mussel Mytilus edulis....... Plant performance varied with light availability but was unaffected by the presence of mussels. Metabolomic analysis, on the other hand, revealed an interaction between light availability and presence of M. edulis on seagrass metabolism. Under high light, mussels stimulated seagrass nitrogen and energy...... metabolism. Conversely, in low light mussels impeded nitrogen and energy metabolism, and enhanced responses against sulfide toxicity, causing inhibited oxidative energy metabolism and tissue degradation. Metabolomic analysis thereby revealed cryptic changes to seagrass condition that could not be detected...

  18. Evaluation of Machine Learning Methods to Predict Coronary Artery Disease Using Metabolomic Data.

    Science.gov (United States)

    Forssen, Henrietta; Patel, Riyaz; Fitzpatrick, Natalie; Hingorani, Aroon; Timmis, Adam; Hemingway, Harry; Denaxas, Spiros

    2017-01-01

    Metabolomic data can potentially enable accurate, non-invasive and low-cost prediction of coronary artery disease. Regression-based analytical approaches however might fail to fully account for interactions between metabolites, rely on a priori selected input features and thus might suffer from poorer accuracy. Supervised machine learning methods can potentially be used in order to fully exploit the dimensionality and richness of the data. In this paper, we systematically implement and evaluate a set of supervised learning methods (L1 regression, random forest classifier) and compare them to traditional regression-based approaches for disease prediction using metabolomic data.

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

    Science.gov (United States)

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

  20. Small Nuclear Co-generation Plants Based on Shipbuilding Technology

    International Nuclear Information System (INIS)

    Vasyukov, V. I.; Veshnyakov, K. B.; Goryunov, E. V.; Zalugin, V. I.; Panov, Yu. K.; Polunichev, V. I.

    2002-01-01

    The development of nuclear cogeneration plants and power desalination complexes of relatively small power, using proven shipbuilding technology, becomes more and more attractive for solving the power supply problems of remote districts of the Extreme North and the Far East with small and medium power grids and for removing the shortage of fresh water in different world regions. The idea of transportation of the power unit with high degree of readiness to the place of its location with minimum construction and mounting activities at the site is very attractive. Compactness typical of RP based on shipbuilding technology allows to develop floating or ground-based plants at minimum use of water area and territory. Small construction scope at the site under conditions of minimum anthropogenic loads and high ecological indices are important arguments in favor of floating nuclear cogeneration plant based on ship power units against the alternative fossil sources. At present, the activities on floating nuclear cogeneration plant design, which is developed on the basis of floating power unit with two KLT-40S reactor plant, which is a modified option of standard KLT-40-type ship plant for icebreaker fleet in Russia are the most advanced. To date, a detailed design of reactor plant has been developed and approved, design activities on floating power unit are in the stage of completion, the site for its location has been selected and licensing by GAN, Russia, is in progress. Besides OKBM has developed some designs of nuclear cogeneration plants of different power on the basis of integral reactor plants, using the experience of transport and stationary power plants designing. Nuclear cogeneration plant investment analysis showed acceptable social and economical efficiency of the design that