NMR-based metabolomics applications

DEFF Research Database (Denmark)

Iaccarino, Nunzia

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

{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.

(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...

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-09-16

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

Using NMR metabolomics to identify responses of an environmental estrogen in blood plasma of fish

International Nuclear Information System (INIS)

Samuelsson, Linda M.; Foerlin, Lars; Karlsson, Goeran; Adolfsson-Erici, Margaretha; Larsson, D.G. Joakim

2006-01-01

Nuclear magnetic resonance (NMR) based metabolomics in combination with multivariate data analysis may become valuable tools to study environmental effects of pharmaceuticals and other chemicals in aquatic organisms. To explore the usefulness of this approach in fish, we have used 1 H NMR metabolomics to compare blood plasma and plasma lipid extracts from rainbow trout exposed to the synthetic contraceptive estrogen ethinylestradiol (EE 2 ) with plasma from control fish. The plasma metabolite profile was affected in fish exposed to 10 ng/L but not 0.87 ng/L of EE 2 , which was in agreement with an induced vitellogenin synthesis in the high dose group only, as measured by ELISA. The main affected metabolites were vitellogenin, alanine, phospholipids and cholesterol. The responses identified by this discovery-driven method could be put in context with previous knowledge of the effects of estrogens on fish. This adds confidence to the approach of using NMR metabolomics to identify environmental effects of pharmaceuticals and other contaminants

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

International Nuclear Information System (INIS)

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

2017-01-01

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

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

Science.gov (United States)

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

2012-08-01

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

NMR-based metabolomics for identification of α-amylase inhibitors in rowan berries (Sorbus spp.)

DEFF Research Database (Denmark)

Broholm, Sofie L.; Gramsbergen, Simone; Nyberg, Nils

Type 2 diabetes is a metabolic disorder estimated to affect millions of people all over the world.1 One way of reducing diabetes-related complications is to control postprandial glucose.2 Inhibition of the carbohydrate digestive enzyme α-amylase is a therapeutic target for maintaining low blood g...... a 1H-NMR method suitable for NMR-based metabolomics...

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

Energy Technology Data Exchange (ETDEWEB)

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

2017-03-20

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

A primer to nutritional metabolomics by NMR spectroscopy and chemometrics

DEFF Research Database (Denmark)

Savorani, Francesco; Rasmussen, Morten Arendt; Mikkelsen, Mette Skau

2013-01-01

This paper outlines the advantages and disadvantages of using high throughput NMR metabolomics for nutritional studies with emphasis on the workflow and data analytical methods for generation of new knowledge. The paper describes one-by-one the major research activities in the interdisciplinary...... metabolomics platform and highlights the opportunities that NMR spectra can provide in future nutrition studies. Three areas are emphasized: (1) NMR as an unbiased and non-destructive platform for providing an overview of the metabolome under investigation, (2) NMR for providing versatile information and data...... structures for multivariate pattern recognition methods and (3) NMR for providing a unique fingerprint of the lipoprotein status of the subject. For the first time in history, by combining NMR spectroscopy and chemometrics we are able to perform inductive nutritional research as a complement to the deductive...

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.

Towards automatic metabolomic profiling of high-resolution one-dimensional proton NMR spectra

International Nuclear Information System (INIS)

Mercier, Pascal; Lewis, Michael J.; Chang, David; Baker, David; Wishart, David S.

2011-01-01

Nuclear magnetic resonance (NMR) and Mass Spectroscopy (MS) are the two most common spectroscopic analytical techniques employed in metabolomics. The large spectral datasets generated by NMR and MS are often analyzed using data reduction techniques like Principal Component Analysis (PCA). Although rapid, these methods are susceptible to solvent and matrix effects, high rates of false positives, lack of reproducibility and limited data transferability from one platform to the next. Given these limitations, a growing trend in both NMR and MS-based metabolomics is towards targeted profiling or “quantitative” metabolomics, wherein compounds are identified and quantified via spectral fitting prior to any statistical analysis. Despite the obvious advantages of this method, targeted profiling is hindered by the time required to perform manual or computer-assisted spectral fitting. In an effort to increase data analysis throughput for NMR-based metabolomics, we have developed an automatic method for identifying and quantifying metabolites in one-dimensional (1D) proton NMR spectra. This new algorithm is capable of using carefully constructed reference spectra and optimizing thousands of variables to reconstruct experimental NMR spectra of biofluids using rules and concepts derived from physical chemistry and NMR theory. The automated profiling program has been tested against spectra of synthetic mixtures as well as biological spectra of urine, serum and cerebral spinal fluid (CSF). Our results indicate that the algorithm can correctly identify compounds with high fidelity in each biofluid sample (except for urine). Furthermore, the metabolite concentrations exhibit a very high correlation with both simulated and manually-detected values.

Towards automatic metabolomic profiling of high-resolution one-dimensional proton NMR spectra

Energy Technology Data Exchange (ETDEWEB)

Mercier, Pascal; Lewis, Michael J.; Chang, David, E-mail: dchang@chenomx.com [Chenomx Inc (Canada); Baker, David [Pfizer Inc (United States); Wishart, David S. [University of Alberta, Department of Computing Science and Biological Sciences (Canada)

2011-04-15

Nuclear magnetic resonance (NMR) and Mass Spectroscopy (MS) are the two most common spectroscopic analytical techniques employed in metabolomics. The large spectral datasets generated by NMR and MS are often analyzed using data reduction techniques like Principal Component Analysis (PCA). Although rapid, these methods are susceptible to solvent and matrix effects, high rates of false positives, lack of reproducibility and limited data transferability from one platform to the next. Given these limitations, a growing trend in both NMR and MS-based metabolomics is towards targeted profiling or 'quantitative' metabolomics, wherein compounds are identified and quantified via spectral fitting prior to any statistical analysis. Despite the obvious advantages of this method, targeted profiling is hindered by the time required to perform manual or computer-assisted spectral fitting. In an effort to increase data analysis throughput for NMR-based metabolomics, we have developed an automatic method for identifying and quantifying metabolites in one-dimensional (1D) proton NMR spectra. This new algorithm is capable of using carefully constructed reference spectra and optimizing thousands of variables to reconstruct experimental NMR spectra of biofluids using rules and concepts derived from physical chemistry and NMR theory. The automated profiling program has been tested against spectra of synthetic mixtures as well as biological spectra of urine, serum and cerebral spinal fluid (CSF). Our results indicate that the algorithm can correctly identify compounds with high fidelity in each biofluid sample (except for urine). Furthermore, the metabolite concentrations exhibit a very high correlation with both simulated and manually-detected values.

NMR-based stable isotope resolved metabolomics in systems biochemistry

International Nuclear Information System (INIS)

Fan, Teresa W-M.; Lane, Andrew N.

2011-01-01

An important goal of metabolomics is to characterize the changes in metabolic networks in cells or various tissues of an organism in response to external perturbations or pathologies. The profiling of metabolites and their steady state concentrations does not directly provide information regarding the architecture and fluxes through metabolic networks. This requires tracer approaches. NMR is especially powerful as it can be used not only to identify and quantify metabolites in an unfractionated mixture such as biofluids or crude cell/tissue extracts, but also determine the positional isotopomer distributions of metabolites derived from a precursor enriched in stable isotopes such as 13 C and 15 N via metabolic transformations. In this article we demonstrate the application of a variety of 2-D NMR editing experiments to define the positional isotopomers of compounds present in polar and non-polar extracts of human lung cancer cells grown in either [U– 13 C]-glucose or [U– 13 C, 15 N]-glutamine as source tracers. The information provided by such experiments enabled unambiguous reconstruction of metabolic pathways, which is the foundation for further metabolic flux modeling.

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.

NMR-based metabolomics of mammalian cell and tissue cultures

Energy Technology Data Exchange (ETDEWEB)

Aranibar, Nelly; Borys, Michael; Mackin, Nancy A.; Ly, Van; Abu-Absi, Nicholas; Abu-Absi, Susan [Bristol-Myers Squibb Company (United States); Niemitz, Matthias [PERCH Solutions Ltd. (Finland); Schilling, Bernhard; Li, Zheng Jian; Brock, Barry; Russell, Reb J.; Tymiak, Adrienne; Reily, Michael D., E-mail: michael.reily@bms.com [Bristol-Myers Squibb Company (United States)

2011-04-15

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.

A guide to the identification of metabolites in NMR-based metabonomics/metabolomics experiments.

Science.gov (United States)

Dona, Anthony C; Kyriakides, Michael; Scott, Flora; Shephard, Elizabeth A; Varshavi, Dorsa; Veselkov, Kirill; Everett, Jeremy R

2016-01-01

Metabonomics/metabolomics is an important science for the understanding of biological systems and the prediction of their behaviour, through the profiling of metabolites. Two technologies are routinely used in order to analyse metabolite profiles in biological fluids: nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS), the latter typically with hyphenation to a chromatography system such as liquid chromatography (LC), in a configuration known as LC-MS. With both NMR and MS-based detection technologies, the identification of the metabolites in the biological sample remains a significant obstacle and bottleneck. This article provides guidance on methods for metabolite identification in biological fluids using NMR spectroscopy, and is illustrated with examples from recent studies on mice.

A guide to the identification of metabolites in NMR-based metabonomics/metabolomics experiments

Directory of Open Access Journals (Sweden)

Anthony C. Dona

2016-01-01

Full Text Available Metabonomics/metabolomics is an important science for the understanding of biological systems and the prediction of their behaviour, through the profiling of metabolites. Two technologies are routinely used in order to analyse metabolite profiles in biological fluids: nuclear magnetic resonance (NMR spectroscopy and mass spectrometry (MS, the latter typically with hyphenation to a chromatography system such as liquid chromatography (LC, in a configuration known as LC–MS. With both NMR and MS-based detection technologies, the identification of the metabolites in the biological sample remains a significant obstacle and bottleneck. This article provides guidance on methods for metabolite identification in biological fluids using NMR spectroscopy, and is illustrated with examples from recent studies on mice.

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

Directory of Open Access Journals (Sweden)

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.

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).

Genetic transformation of rare Verbascum eriophorum Godr. plants and metabolic alterations revealed by NMR-based metabolomics.

Science.gov (United States)

Marchev, Andrey; Yordanova, Zhenya; Alipieva, Kalina; Zahmanov, Georgi; Rusinova-Videva, Snezhana; Kapchina-Toteva, Veneta; Simova, Svetlana; Popova, Milena; Georgiev, Milen I

2016-09-01

To develop a protocol to transform Verbascum eriophorum and to study the metabolic differences between mother plants and hairy root culture by applying NMR and processing the datasets with chemometric tools. Verbascum eriophorum is a rare species with restricted distribution, which is poorly studied. Agrobacterium rhizogenes-mediated genetic transformation of V. eriophorum and hairy root culture induction are reported for the first time. To determine metabolic alterations, V. eriophorum mother plants and relevant hairy root culture were subjected to comprehensive metabolomic analyses, using NMR (1D and 2D). Metabolomics data, processed using chemometric tools (and principal component analysis in particular) allowed exploration of V. eriophorum metabolome and have enabled identification of verbascoside (by means of 2D-TOCSY NMR) as the most abundant compound in hairy root culture. Metabolomics data contribute to the elucidation of metabolic alterations after T-DNA transfer to the host V. eriophorum genome and the development of hairy root culture for sustainable bioproduction of high value verbascoside.

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.

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

Science.gov (United States)

Rist, Manuela J; Muhle-Goll, Claudia; Görling, Benjamin; Bub, Achim; Heissler, Stefan; Watzl, Bernhard; Luy, Burkhard

2013-04-09

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.

NMR and pattern recognition methods in metabolomics: From data acquisition to biomarker discovery: A review

Energy Technology Data Exchange (ETDEWEB)

Smolinska, Agnieszka, E-mail: A.Smolinska@science.ru.nl [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands); Blanchet, Lionel [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands); Department of Biochemistry, Nijmegen Centre for Molecular Life Sciences, Radboud University Nijmegen Medical Centre, Nijmegen (Netherlands); Buydens, Lutgarde M.C.; Wijmenga, Sybren S. [Institute for Molecules and Materials, Radboud University Nijmegen, Nijmegen (Netherlands)

2012-10-31

Highlights: Black-Right-Pointing-Pointer Procedures for acquisition of different biofluids by NMR. Black-Right-Pointing-Pointer Recent developments in metabolic profiling of different biofluids by NMR are presented. Black-Right-Pointing-Pointer The crucial steps involved in data preprocessing and multivariate chemometric analysis are reviewed. Black-Right-Pointing-Pointer 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).

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.

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.; Luchinat, Claudio; Turano, Paola; Tenori, Leonardo; Roy, Raja; Salek, Reza M.; Ryan, Danielle; Merzaban, Jasmeen; Kaddurah-Daouk, Rima; Zeri, Ana Carolina; Nagana Gowda, G. A.; Raftery, Daniel; Wang, Yulan; Brennan, Lorraine; Wishart, David S.

2014-01-01

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.

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

Science.gov (United States)

Emwas, Abdul-Hamid; Luchinat, Claudio; Turano, Paola; Tenori, Leonardo; Roy, Raja; Salek, Reza M; Ryan, Danielle; Merzaban, Jasmeen S; Kaddurah-Daouk, Rima; Zeri, Ana Carolina; Nagana Gowda, G A; Raftery, Daniel; Wang, Yulan; Brennan, Lorraine; Wishart, David S

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.

NMR and MS Methods for Metabolomics.

Science.gov (United States)

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

2017-01-01

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

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.

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

Directory of Open Access Journals (Sweden)

Emanuela Locci

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

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.

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.

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

KAUST Repository

Emwas, Abdul-Hamid M.; 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.

2016-01-01

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.

Metabolic effects of basic fibroblast growth factor in streptozotocin-induced diabetic rats: A 1H NMR-based metabolomics investigation

OpenAIRE

Lin, Xiaodong; Zhao, Liangcai; Tang, Shengli; Zhou, Qi; Lin, Qiuting; Li, Xiaokun; Zheng, Hong; Gao, Hongchang

2016-01-01

The fibroblast growth factors (FGFs) family shows a great potential in the treatment of diabetes, but little attention is paid to basic FGF (bFGF). In this study, to explore the metabolic effects of bFGF on diabetes, metabolic changes in serum and feces were analyzed in the normal rats, the streptozocin (STZ)-induced diabetic rats and the bFGF-treated diabetic rats using a 1H nuclear magnetic resonance (NMR)-based metabolomic approach. Interestingly, bFGF treatment significantly decreased glu...

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

Science.gov (United States)

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

2016-05-01

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

Toxic responses of Perna viridis hepatopancreas exposed to DDT, benzo(a)pyrene and their mixture uncovered by iTRAQ-based proteomics and NMR-based metabolomics.

Science.gov (United States)

Song, Qinqin; Zhou, Hailong; Han, Qian; Diao, Xiaoping

2017-11-01

Dichlorodiphenyltrichloroethane (DDT) and benzo(a)pyrene (BaP) are environmental estrogens (EEs) that are ubiquitous in the marine environment. In the present study, we integrated isobaric tags for relative and absolute quantitation (iTRAQ)-based proteomic and nuclear magnetic resonance (NMR)-based metabolomic approaches to explore the toxic responses of green mussel hepatopancreas exposed to DDT (10μg/L), BaP (10μg/L) and their mixture. The metabolic responses indicated that BaP primarily disturbed energy metabolism and osmotic regulation in the hepatopancreas of the male green mussel P. viridis. Both DDT and the mixture of DDT and BaP perturbed the energy metabolism and osmotic regulation in P. viridis. The proteomic responses revealed that BaP affected the proteins involved in energy metabolism, material transformation, cytoskeleton, stress responses, reproduction and development in green mussels. DDT exposure could change the proteins involved in primary metabolism, stress responses, cytoskeleton and signal transduction. However, the mixture of DDT and BaP altered proteins associated with material and energy metabolism, stress responses, signal transduction, reproduction and development, cytoskeleton and apoptosis. This study showed that iTRAQ-based proteomic and NMR-based metabolomic approaches could effectively elucidate the essential molecular mechanism of disturbances in hepatopancreas function of green mussels exposed to environmental estrogens. Copyright © 2017 Elsevier B.V. All rights reserved.

Rapid discrimination of strain-dependent fermentation characteristics among Lactobacillus strains by NMR-based metabolomics of fermented vegetable juice.

Directory of Open Access Journals (Sweden)

Satoru Tomita

Full Text Available In this study, we investigated the applicability of NMR-based metabolomics to discriminate strain-dependent fermentation characteristics of lactic acid bacteria (LAB, which are important microorganisms for fermented food production. To evaluate the discrimination capability, six type strains of Lactobacillus species and six additional L. brevis strains were used focusing on i the difference between homo- and hetero-lactic fermentative species and ii strain-dependent characteristics within L. brevis. Based on the differences in the metabolite profiles of fermented vegetable juices, non-targeted principal component analysis (PCA clearly separated the samples into those inoculated with homo- and hetero-lactic fermentative species. The separation was primarily explained by the different levels of dominant metabolites (lactic acid, acetic acid, ethanol, and mannitol. Orthogonal partial least squares discrimination analysis, based on a regions-of-interest (ROIs approach, revealed the contribution of low-abundance metabolites: acetoin, phenyllactic acid, p-hydroxyphenyllactic acid, glycerophosphocholine, and succinic acid for homolactic fermentation; and ornithine, tyramine, and γ-aminobutyric acid (GABA for heterolactic fermentation. Furthermore, ROIs-based PCA of seven L. brevis strains separated their strain-dependent fermentation characteristics primarily based on their ability to utilize sucrose and citric acid, and convert glutamic acid and tyrosine into GABA and tyramine, respectively. In conclusion, NMR metabolomics successfully discriminated the fermentation characteristics of the tested strains and provided further information on metabolites responsible for these characteristics, which may impact the taste, aroma, and functional properties of fermented foods.

1H NMR-based metabolomics investigation on the effects of petrochemical contamination in posterior adductor muscles of caged mussel Mytilus galloprovincialis.

Science.gov (United States)

Cappello, Tiziana; Maisano, Maria; Mauceri, Angela; Fasulo, Salvatore

2017-08-01

Environmental metabolomics is a high-throughout approach that provides a snapshot of the metabolic status of an organism. In order to elucidate the biological effects of petrochemical contamination on aquatic invertebrates, mussels Mytilus galloprovincialis were caged at the "Augusta-Melilli-Priolo" petrochemical area and Brucoli (Sicily, south Italy), chosen as the reference site. After confirming the elevated concentrations of polycyclic aromatic hydrocarbons (PAHs) and mercury (Hg) in Augusta sediments in our previous work (Maisano et al., 2016a), herein an environmental metabolomics approach based on protonic nuclear magnetic resonance ( 1 H NMR), coupled with chemometrics, was applied on the mussel posterior adductor muscle (PAM), the main muscular system in bivalve molluscs. Amino acids, osmolytes, energy storage compounds, tricarboxylic acid cycle intermediates, and nucleotides, were found in PAM NMR spectra. Principal Component Analysis (PCA) indicated that mussels caged at the polluted site clustered separately from mussels from the control area, suggesting a clear differentiation between their metabolic profiles. Specifically, disorders in energy metabolism, alterations in amino acids metabolism, and disturbance in the osmoregulatory processes were observed in mussel PAM. Overall, findings from this work demonstrated the usefulness of applying an active biomonitoring strategy for environmental risk assessment, and the effectiveness of metabolomics in elucidating changes in metabolic pathways of aquatic organisms caged at sites differentially contaminated, and thus its suitability to be applied in ecotoxicological studies. Copyright © 2017 Elsevier Inc. All rights reserved.

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-02-18

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

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

International Nuclear Information System (INIS)

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

2016-01-01

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

NMR metabolomics for assessment of exercise effects with mouse biofluids

Energy Technology Data Exchange (ETDEWEB)

Le Moyec, Laurence; Mille-Hamard, Laurence; Breuneval, Carole; Petot, Helene; Billat, Veronique L. [Universite Evry Val d' Essonne, UBIAE INSERM U902, Evry Cedex (France); Triba, Mohamed N. [Universite Paris 13, CSPBAT UMR 7244, Bobigny (France)

2012-08-15

Exercise modulates the metabolome in urine or blood as demonstrated previously for humans and animal models. Using nuclear magnetic resonance (NMR) metabolomics, the present study compares the metabolic consequences of an exhaustive exercise at peak velocity (Vp) and at critical velocity (Vc) on mice. Since small-volume samples (blood and urine) were collected, dilution was necessary to acquire NMR spectra. Consequently, specific processing methods were applied before statistical analysis. According to the type of exercise (control group, Vp group and Vc group), 26 male mice were divided into three groups. Mice were sacrificed 2 h after the end of exercise, and urine and blood samples were drawn from each mouse. Proton NMR spectra were acquired with urine and deproteinized blood. The NMR data were aligned with the icoshift method and normalised using the probabilistic quotient method. Finally, data were analysed with the orthogonal projection of latent-structure analysis. The spectra obtained with deproteinized blood can neither discriminate the control mice from exercised mice nor discriminate according to the duration of the exercise. With urine samples, a significant statistical model can be estimated when comparing the control mice to both groups, Vc and Vp. The best model is obtained according to the exercise duration with all mice. Taking into account the spectral regions having the highest correlations, the discriminant metabolites are allantoin, inosine and branched-chain amino acids. In conclusion, metabolomic profiles assessed with NMR are highly dependent on the exercise. These results show that urine samples are more informative than blood samples and that the duration of the exercise is a more important parameter to influence the metabolomic status than the exercise velocity. (orig.)

Assessing Heterogeneity of Osteolytic Lesions in Multiple Myeloma by 1H HR-MAS NMR Metabolomics

Directory of Open Access Journals (Sweden)

Laurette Tavel

2016-10-01

Full Text Available Multiple myeloma (MM is a malignancy of plasma cells characterized by multifocal osteolytic bone lesions. Macroscopic and genetic heterogeneity has been documented within MM lesions. Understanding the bases of such heterogeneity may unveil relevant features of MM pathobiology. To this aim, we deployed unbiased 1H high-resolution magic-angle spinning (HR-MAS nuclear magnetic resonance (NMR metabolomics to analyze multiple biopsy specimens of osteolytic lesions from one case of pathological fracture caused by MM. Multivariate analyses on normalized metabolite peak integrals allowed clusterization of samples in accordance with a posteriori histological findings. We investigated the relationship between morphological and NMR features by merging morphological data and metabolite profiling into a single correlation matrix. Data-merging addressed tissue heterogeneity, and greatly facilitated the mapping of lesions and nearby healthy tissues. Our proof-of-principle study reveals integrated metabolomics and histomorphology as a promising approach for the targeted study of osteolytic lesions.

MetaboLab - advanced NMR data processing and analysis for metabolomics

Directory of Open Access Journals (Sweden)

Günther Ulrich L

2011-09-01

Full Text Available Abstract Background Despite wide-spread use of Nuclear Magnetic Resonance (NMR in metabolomics for the analysis of biological samples there is a lack of graphically driven, publicly available software to process large one and two-dimensional NMR data sets for statistical analysis. Results Here we present MetaboLab, a MATLAB based software package that facilitates NMR data processing by providing automated algorithms for processing series of spectra in a reproducible fashion. A graphical user interface provides easy access to all steps of data processing via a script builder to generate MATLAB scripts, providing an option to alter code manually. The analysis of two-dimensional spectra (1H,13C-HSQC spectra is facilitated by the use of a spectral library derived from publicly available databases which can be extended readily. The software allows to display specific metabolites in small regions of interest where signals can be picked. To facilitate the analysis of series of two-dimensional spectra, different spectra can be overlaid and assignments can be transferred between spectra. The software includes mechanisms to account for overlapping signals by highlighting neighboring and ambiguous assignments. Conclusions The MetaboLab software is an integrated software package for NMR data processing and analysis, closely linked to the previously developed NMRLab software. It includes tools for batch processing and gives access to a wealth of algorithms available in the MATLAB framework. Algorithms within MetaboLab help to optimize the flow of metabolomics data preparation for statistical analysis. The combination of an intuitive graphical user interface along with advanced data processing algorithms facilitates the use of MetaboLab in a broader metabolomics context.

The application of micro-coil NMR probe technology to metabolomics of urine and serum

International Nuclear Information System (INIS)

Grimes, John H.; O’Connell, Thomas M.

2011-01-01

Increasing the sensitivity and throughput of NMR-based metabolomics is critical for the continued growth of this field. In this paper the application of micro-coil NMR probe technology was evaluated for this purpose. The most commonly used biofluids in metabolomics are urine and serum. In this study we examine different sample limited conditions and compare the detection sensitivity of the micro-coil with a standard 5 mm NMR probe. Sample concentration is evaluated as a means to leverage the greatly improved mass sensitivity of the micro-coil probes. With very small sample volumes, the sensitivity of the micro-coil probe does indeed provide a significant advantage over the standard probe. Concentrating the samples does improve the signal detection, but the benefits do not follow the expected linear increase and are both matrix and metabolite specific. Absolute quantitation will be affected by concentration, but an analysis of relative concentrations is still possible. The choice of the micro-coil probe over a standard tube based probe will depend upon a number of factors including number of samples and initial volume but this study demonstrates the feasibility of high-throughput metabolomics with the micro-probe platform.

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.

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.

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

Accurate, fully-automated NMR spectral profiling for metabolomics.

Directory of Open Access Journals (Sweden)

Siamak Ravanbakhsh

Full Text Available Many diseases cause significant changes to the concentrations of small molecules (a.k.a. metabolites that appear in a person's biofluids, which means such diseases can often be readily detected from a person's "metabolic profile"-i.e., the list of concentrations of those metabolites. This information can be extracted from a biofluids Nuclear Magnetic Resonance (NMR spectrum. However, due to its complexity, NMR spectral profiling has remained manual, resulting in slow, expensive and error-prone procedures that have hindered clinical and industrial adoption of metabolomics via NMR. This paper presents a system, BAYESIL, which can quickly, accurately, and autonomously produce a person's metabolic profile. Given a 1D 1H NMR spectrum of a complex biofluid (specifically serum or cerebrospinal fluid, BAYESIL can automatically determine the metabolic profile. This requires first performing several spectral processing steps, then matching the resulting spectrum against a reference compound library, which contains the "signatures" of each relevant metabolite. BAYESIL views spectral matching as an inference problem within a probabilistic graphical model that rapidly approximates the most probable metabolic profile. Our extensive studies on a diverse set of complex mixtures including real biological samples (serum and CSF, defined mixtures and realistic computer generated spectra; involving > 50 compounds, show that BAYESIL can autonomously find the concentration of NMR-detectable metabolites accurately (~ 90% correct identification and ~ 10% quantification error, in less than 5 minutes on a single CPU. These results demonstrate that BAYESIL is the first fully-automatic publicly-accessible system that provides quantitative NMR spectral profiling effectively-with an accuracy on these biofluids that meets or exceeds the performance of trained experts. We anticipate this tool will usher in high-throughput metabolomics and enable a wealth of new applications of

Impact of metal pollution on shrimp Crangon affinis by NMR-based metabolomics

International Nuclear Information System (INIS)

Ji, Chenglong; Yu, Deliang; Wang, Qing; Li, Fei; Zhao, Jianmin; Wu, Huifeng

2016-01-01

Both cadmium and arsenic are the important metal/metalloid pollutants in the Bohai Sea. In this work, we sampled the dominant species, shrimp Crangon affinis, from three sites, the Middle of the Bohai Sea (MBS), the Yellow River Estuary (YRE) and the Laizhou Bay (LZB) along the Bohai Sea. The concentrations of metals/metalloids in shrimps C. affinis indicated that the YRE site was polluted by Cd and Pb, while the LZB site was contaminated by As. The metabolic differences between shrimps C. affinis from the reference site (MBS) and metal-pollution sites (YRE and LZB) were characterized using NMR-based metabolomics. Results indicated that the metal pollutions in YRE and LZB induced disturbances in osmotic regulation and energy metabolism via different metabolic pathways. In addition, a combination of alanine and arginine might be the biomarker of Cd contamination, while BCAAs and tyrosine could be the biomarkers of arsenic contamination in C. affinis. - Highlights: •YRE and LZB are mainly polluted by Cd and As, respectively. •Metal pollutions caused differential effects in C. affinis from different sites. •Metabolomics is useful to elucidate metal pollution-induced biological effects.

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

Energy Technology Data Exchange (ETDEWEB)

2016-10-18

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

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.

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.

Metabolomic NMR fingerprinting to identify and predict survival of patients with metastatic colorectal cancer

DEFF Research Database (Denmark)

Bertini, Ivano; Cacciatore, Stefano; Jensen, Benny V

2012-01-01

Earlier detection of patients with metastatic colorectal cancer (mCRC) might improve their treatment and survival outcomes. In this study, we used proton nuclear magnetic resonance ((1)H-NMR) to profile the serum metabolome in patients with mCRC and determine whether a disease signature may exist...... survival (HR, 3.4; 95% confidence interval, 2.06-5.50; P = 1.33 × 10(-6)). A number of metabolites concurred with the (1)H-NMR fingerprint of mCRC, offering insights into mCRC metabolic pathways. Our findings establish that (1)H-NMR profiling of patient serum can provide a strong metabolomic signature of m...

Insights into the impact of silver nanoparticles on human keratinocytes metabolism through NMR metabolomics.

Science.gov (United States)

Carrola, Joana; Bastos, Verónica; Ferreira de Oliveira, José Miguel P; Oliveira, Helena; Santos, Conceição; Gil, Ana M; Duarte, Iola F

2016-01-01

Due to their antimicrobial properties, silver nanoparticles (AgNPs) are increasingly incorporated into consumer goods and medical products. Their potential toxicity to human cells is however a major concern, and there is a need for improved understanding of their effects on cell metabolism and function. Here, Nuclear Magnetic Resonance (NMR) metabolomics was used to investigate the metabolic profile of human epidermis keratinocytes (HaCaT cell line) exposed for 48 h to 30 nm citrate-stabilized spherical AgNPs (10 and 40 μg/mL). Intracellular aqueous extracts, organic extracts and extracellular culture medium were analysed to provide an integrated view of the cellular metabolic response. The specific metabolite variations, highlighted through multivariate analysis and confirmed by spectral integration, suggested that HaCaT cells exposed to AgNPs displayed upregulated glutathione-based antioxidant protection, increased glutaminolysis, downregulated tricarboxylic acid (TCA) cycle activity, energy depletion and cell membrane modification. Importantly, most metabolic changes were apparent in cells exposed to a concentration of AgNPs which did not affect cell viability at significant levels, thus underlying the sensitivity of NMR metabolomics to detect early biochemical events, even in the absence of a clear cytotoxic response. It can be concluded that NMR metabolomics is an important new tool in the field of in vitro nanotoxicology. Copyright © 2015 Elsevier Inc. All rights reserved.

Improving Visualization and Interpretation of Metabolome-Wide Association Studies: An Application in a Population-Based Cohort Using Untargeted 1H NMR Metabolic Profiling.

Science.gov (United States)

Castagné, Raphaële; Boulangé, Claire Laurence; Karaman, Ibrahim; Campanella, Gianluca; Santos Ferreira, Diana L; Kaluarachchi, Manuja R; Lehne, Benjamin; Moayyeri, Alireza; Lewis, Matthew R; Spagou, Konstantina; Dona, Anthony C; Evangelos, Vangelis; Tracy, Russell; Greenland, Philip; Lindon, John C; Herrington, David; Ebbels, Timothy M D; Elliott, Paul; Tzoulaki, Ioanna; Chadeau-Hyam, Marc

2017-10-06

1 H NMR spectroscopy of biofluids generates reproducible data allowing detection and quantification of small molecules in large population cohorts. Statistical models to analyze such data are now well-established, and the use of univariate metabolome wide association studies (MWAS) investigating the spectral features separately has emerged as a computationally efficient and interpretable alternative to multivariate models. The MWAS rely on the accurate estimation of a metabolome wide significance level (MWSL) to be applied to control the family wise error rate. Subsequent interpretation requires efficient visualization and formal feature annotation, which, in-turn, call for efficient prioritization of spectral variables of interest. Using human serum 1 H NMR spectroscopic profiles from 3948 participants from the Multi-Ethnic Study of Atherosclerosis (MESA), we have performed a series of MWAS for serum levels of glucose. We first propose an extension of the conventional MWSL that yields stable estimates of the MWSL across the different model parameterizations and distributional features of the outcome. We propose both efficient visualization methods and a strategy based on subsampling and internal validation to prioritize the associations. Our work proposes and illustrates practical and scalable solutions to facilitate the implementation of the MWAS approach and improve interpretation in large cohort studies.

NMR Techniques in Metabolomic Studies: A Quick Overview on Examples of Utilization.

Science.gov (United States)

Kruk, Joanna; Doskocz, Marek; Jodłowska, Elżbieta; Zacharzewska, Anna; Łakomiec, Joanna; Czaja, Kornelia; Kujawski, Jacek

2017-01-01

Metabolomics is a rapidly developing branch of science that concentrates on identifying biologically active molecules with potential biomarker properties. To define the best biomarkers for diseases, metabolomics uses both models (in vitro, animals) and human, as well as, various techniques such as mass spectroscopy, gas chromatography, liquid chromatography, infrared and UV-VIS spectroscopy and nuclear magnetic resonance. The last one takes advantage of the magnetic properties of certain nuclei, such as 1 H, 13 C, 31 P, 19 F, especially their ability to absorb and emit energy, what is crucial for analyzing samples. Among many spectroscopic NMR techniques not only one-dimensional (1D) techniques are known, but for many years two-dimensional (2D, for example, COSY, DOSY, JRES, HETCORE, HMQS), three-dimensional (3D, DART-MS, HRMAS, HSQC, HMBC) and solid-state NMR have been used. In this paper, authors taking apart fundamental division of nuclear magnetic resonance techniques intend to shown their wide application in metabolomic studies, especially in identifying biomarkers.

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

Science.gov (United States)

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

2016-03-01

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

Assessment of 1H NMR-based metabolomics analysis for normalization of urinary metals against creatinine.

Science.gov (United States)

Cassiède, Marc; Nair, Sindhu; Dueck, Meghan; Mino, James; McKay, Ryan; Mercier, Pascal; Quémerais, Bernadette; Lacy, Paige

2017-01-01

Proton nuclear magnetic resonance ( 1 H NMR, or NMR) spectroscopy and inductively coupled plasma-mass spectrometry (ICP-MS) are commonly used for metabolomics and metal analysis in urine samples. However, creatinine quantification by NMR for the purpose of normalization of urinary metals has not been validated. We assessed the validity of using NMR analysis for creatinine quantification in human urine samples in order to allow normalization of urinary metal concentrations. NMR and ICP-MS techniques were used to measure metabolite and metal concentrations in urine samples from 10 healthy subjects. For metabolite analysis, two magnetic field strengths (600 and 700MHz) were utilized. In addition, creatinine concentrations were determined by using the Jaffe method. Creatinine levels were strongly correlated (R 2 =0.99) between NMR and Jaffe methods. The NMR spectra were deconvoluted with a target database containing 151 metabolites that are present in urine. A total of 50 metabolites showed good correlation (R 2 =0.7-1.0) at 600 and 700MHz. Metal concentrations determined after NMR-measured creatinine normalization were comparable to previous reports. NMR analysis provided robust urinary creatinine quantification, and was sufficient for normalization of urinary metal concentrations. We found that NMR-measured creatinine-normalized urinary metal concentrations in our control subjects were similar to general population levels in Canada and the United Kingdom. Copyright © 2016 Elsevier B.V. All rights reserved.

[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.

Metabolomics study of Saw palmetto extracts based on 1H NMR spectroscopy.

Science.gov (United States)

de Combarieu, Eric; Martinelli, Ernesto Marco; Pace, Roberto; Sardone, Nicola

2015-04-01

Preparations containing Saw palmetto extracts are used in traditional medicine to treat benign prostatic hyperplasia. According to the European and the American Pharmacopoeias, the extract is obtained from comminuted Saw palmetto berries by a suitable extracting procedure using ethanol or supercritical carbon dioxide or a mixture of n-hexane and methylpentanes. In the present study an approach to metabolomics profiling using nuclear magnetic resonance (NMR) has been used as a finger-printing tool to assess the overall composition of the extracts. The phytochemical analysis coupled with principal component analysis (PCA) showed the same composition of the Saw palmetto extracts obtained with carbon dioxide and hexane with minor not significant differences for extracts obtained with ethanol. In fact these differences are anyhow lower than the batch-to-batch variability ascribable to the natural-occurring variability in the Saw palmetto fruits' phytochemical composition. The fingerprinting analysis combined with chemometric method, is a technique, which would provide a tool to comprehensively assess the quality control of Saw palmetto extracts. Copyright © 2015 Elsevier B.V. All rights reserved.

Metabolomic Characterization of Ovarian Epithelial Carcinomas by HRMAS-NMR Spectroscopy

Directory of Open Access Journals (Sweden)

D. Ben Sellem

2011-01-01

Full Text Available Objectives. The objectives of the present study are to determine if a metabolomic study by HRMAS-NMR can (i discriminate between different histological types of epithelial ovarian carcinomas and healthy ovarian tissue, (ii generate statistical models capable of classifying borderline tumors and (iii establish a potential relationship with patient's survival or response to chemotherapy. Methods. 36 human epithelial ovarian tumor biopsies and 3 healthy ovarian tissues were studied using 1H HRMAS NMR spectroscopy and multivariate statistical analysis. Results. The results presented in this study demonstrate that the three histological types of epithelial ovarian carcinomas present an effective metabolic pattern difference. Furthermore, a metabolic signature specific of serous (N-acetyl-aspartate and mucinous (N-acetyl-lysine carcinomas was found. The statistical models generated in this study are able to predict borderline tumors characterized by an intermediate metabolic pattern similar to the normal ovarian tissue. Finally and importantly, the statistical model of serous carcinomas provided good predictions of both patient's survival rates and the patient's response to chemotherapy. Conclusions. Despite the small number of samples used in this study, the results indicate that metabolomic analysis of intact tissues by HRMAS-NMR is a promising technique which might be applicable to the therapeutic management of patients.

Knowns and unknowns in metabolomics identified by multidimensional NMR and hybrid MS/NMR methods

Energy Technology Data Exchange (ETDEWEB)

Bingol, Kerem; Brüschweiler, Rafael

2017-02-01

Metabolomics continues to make rapid progress through the development of new and better methods and their applications to gain insight into the metabolism of a wide range of different biological systems from a systems biology perspective. Customization of NMR databases and search tools allows the faster and more accurate identification of known metabolites, whereas the identification of unknowns, without a need for extensive purification, requires new strategies to integrate NMR with mass spectrometry, cheminformatics, and computational methods. For some applications, the use of covalent and non-covalent attachments in the form of labeled tags or nanoparticles can significantly reduce the complexity of these tasks.

Association between the metabolome and low bone mineral density in Taiwanese women determined by (1)H NMR spectroscopy.

Science.gov (United States)

You, Ying-Shu; Lin, Ching-Yu; Liang, Hao-Jan; Lee, Shen-Hung; Tsai, Keh-Sung; Chiou, Jeng-Min; Chen, Yen-Ching; Tsao, Chwen-Keng; Chen, Jen-Hau

2014-01-01

Osteoporosis is related to the alteration of specific circulating metabolites. However, previous studies on only a few metabolites inadequately explain the pathogenesis of this complex syndrome. To date, no study has related the metabolome to bone mineral density (BMD), which would provide an overview of metabolism status and may be useful in clinical practice. This cross-sectional study involved 601 healthy Taiwanese women aged 40 to 55 years recruited from MJ Health Management Institution between 2009 and 2010. Participants were classified according to high (2nd tertile plus 3rd tertile) and low (1st tertile) BMD groups. The plasma metabolome was evaluated by proton nuclear magnetic resonance spectroscopy ((1) H NMR). Principal components analysis (PCA), partial least-squares discriminant analysis (PLS-DA), and logistic regression analysis were used to assess the association between the metabolome and BMD. The high and low BMD groups could be differentiated by PLS-DA but not PCA in postmenopausal women (Q(2)  = 0.05, ppermutation  = 0.04). Among postmenopausal women, elevated glutamine was significantly associated with low BMD (adjusted odds ratio [AOR] = 5.10); meanwhile, elevated lactate (AOR = 0.55), acetone (AOR = 0.51), lipids (AOR = 0.04), and very low-density lipoprotein (AOR = 0.49) protected against low BMD. To the best of our knowledge, this study is the first to identify a group of metabolites for characterizing low BMD in postmenopausal women using a (1) H NMR-based metabolomic approach. The metabolic profile may be useful for predicting the risk of osteoporosis in postmenopausal women at an early age. © 2014 American Society for Bone and Mineral Research.

Updates in metabolomics tools and resources: 2014-2015.

Science.gov (United States)

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

2016-01-01

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

CRAFT (complete reduction to amplitude frequency table)--robust and time-efficient Bayesian approach for quantitative mixture analysis by NMR.

Science.gov (United States)

Krishnamurthy, Krish

2013-12-01

The intrinsic quantitative nature of NMR is increasingly exploited in areas ranging from complex mixture analysis (as in metabolomics and reaction monitoring) to quality assurance/control. Complex NMR spectra are more common than not, and therefore, extraction of quantitative information generally involves significant prior knowledge and/or operator interaction to characterize resonances of interest. Moreover, in most NMR-based metabolomic experiments, the signals from metabolites are normally present as a mixture of overlapping resonances, making quantification difficult. Time-domain Bayesian approaches have been reported to be better than conventional frequency-domain analysis at identifying subtle changes in signal amplitude. We discuss an approach that exploits Bayesian analysis to achieve a complete reduction to amplitude frequency table (CRAFT) in an automated and time-efficient fashion - thus converting the time-domain FID to a frequency-amplitude table. CRAFT uses a two-step approach to FID analysis. First, the FID is digitally filtered and downsampled to several sub FIDs, and secondly, these sub FIDs are then modeled as sums of decaying sinusoids using the Bayesian approach. CRAFT tables can be used for further data mining of quantitative information using fingerprint chemical shifts of compounds of interest and/or statistical analysis of modulation of chemical quantity in a biological study (metabolomics) or process study (reaction monitoring) or quality assurance/control. The basic principles behind this approach as well as results to evaluate the effectiveness of this approach in mixture analysis are presented. Copyright © 2013 John Wiley & Sons, Ltd.

“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

Toxic actions of dinoseb in medaka (Oryzias latipes) embryos as determined by in vivo 31P NMR, HPLC-UV and 1H NMR metabolomics.

Science.gov (United States)

Viant, Mark R; Pincetich, Christopher A; Hinton, David E; Tjeerdema, Ronald S

2006-03-10

Changes in metabolism of Japanese medaka (Oryzias latipes) embryos exposed to dinoseb (2-sec-butyl-4,6-dinitrophenol), a substituted dinitrophenol herbicide, were determined by in vivo (31)P NMR, high-pressure liquid chromatography (HPLC)-UV, and (1)H NMR metabolomics. ATP and phosphocreatine (PCr) metabolism were characterized within intact embryos by in vivo (31)P NMR; concentrations of ATP, GTP, ADP, GDP, AMP and PCr were determined by HPLC-UV; and changes in numerous polar metabolites were characterized by (1)H NMR-based metabolomics. Rangefinding exposures determined two sublethal doses of dinoseb, 50 and 75 ppb, in which embryos survived from 1-day post fertilization (DPF) through the duration of embryogenesis. In vivo (31)P NMR data were acquired from 900 embryos in 0, 50, and 75 ppb dinoseb at 14, 62, and 110 h (n = 6 groups) after initiation of exposure. After 110 h, embryos were observed for normal development and hatching success, then either preserved in 10% formalin for growth analysis or flash frozen and extracted for HPLC-UV and (1)H NMR analysis. Dinoseb exposure at both concentrations resulted in significant declines in [ATP] and [PCr] at 110 h as measured by in vivo (31)P NMR (p fashion. Metabolic effects measured by in vivo (31)P NMR showed a significant increase in orthophosphate levels (P(i); p < 0.05), and significant decreases in [ATP], [PCr] and the PCr/P(i) ratio (p < 0.05). Metabolomics revealed a dose-response relationship between dinoseb and endogenous metabolite changes, with both dinoseb concentrations producing significantly different metabolic profiles from controls (p < 0.05). Metabolic changes included decreased concentrations of ATP, PCr, alanine and tyrosine, and increased concentrations of lactate with medaka embryotoxicity. This study demonstrated that medaka embryos respond to dinoseb with significant changes in metabolism, reduced growth and heart rates, and increased abnormal development and post-exposure mortality. All

NMR metabolomics of ripened and developing oilseed rape (Brassica napus) and turnip rape (Brassica rapa).

Science.gov (United States)

Kortesniemi, Maaria; Vuorinen, Anssi L; Sinkkonen, Jari; Yang, Baoru; Rajala, Ari; Kallio, Heikki

2015-04-01

The oilseeds of the commercially important oilseed rape (Brassica napus) and turnip rape (Brassica rapa) were investigated with (1)H NMR metabolomics. The compositions of ripened (cultivated in field trials) and developing seeds (cultivated in controlled conditions) were compared in multivariate models using principal component analysis (PCA), partial least squares discriminant analysis (PLS-DA), and orthogonal partial least squares discriminant analysis (OPLS-DA). Differences in the major lipids and the minor metabolites between the two species were found. A higher content of polyunsaturated fatty acids and sucrose were observed in turnip rape, while the overall oil content and sinapine levels were higher in oilseed rape. The genotype traits were negligible compared to the effect of the growing site and concomitant conditions on the oilseed metabolome. This study demonstrates the applicability of NMR-based analysis in determining the species, geographical origin, developmental stage, and quality of oilseed Brassicas. Copyright © 2014 Elsevier Ltd. All rights reserved.

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.

"1H-NMR-based metabolomics studies of the toxicity of mesoporous carbon nanoparticles in Zebrafish (Daniorerio)

International Nuclear Information System (INIS)

Raja, Ganesan; Kim, Si Won; Yoon, Da Hye; Yoon, Chang Shin; Kim, Suhkmann

2017-01-01

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 "1H-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

Monitoring Metabolite Profiles of Cannabis sativa L. Trichomes during Flowering Period Using 1H NMR-Based Metabolomics and Real-Time PCR.

Science.gov (United States)

Happyana, Nizar; Kayser, Oliver

2016-08-01

Cannabis sativa trichomes are glandular structures predominantly responsible for the biosynthesis of cannabinoids, the biologically active compounds unique to this plant. To the best of our knowledge, most metabolomic works on C. sativa that have been reported previously focused their investigations on the flowers and leaves of this plant. In this study, (1)H NMR-based metabolomics and real-time PCR analysis were applied for monitoring the metabolite profiles of C. sativa trichomes, variety Bediol, during the last 4 weeks of the flowering period. Partial least squares discriminant analysis models successfully classified metabolites of the trichomes based on the harvest time. Δ (9)-Tetrahydrocannabinolic acid (1) and cannabidiolic acid (2) constituted the vital differential components of the organic preparations, while asparagine, glutamine, fructose, and glucose proved to be their water-extracted counterparts. According to RT-PCR analysis, gene expression levels of olivetol synthase and olivetolic acid cyclase influenced the accumulation of cannabinoids in the Cannabis trichomes during the monitoring time. Moreover, quantitative (1)H NMR and RT-PCR analysis of the Cannabis trichomes suggested that the gene regulation of cannabinoid biosynthesis in the C. sativa variety Bediol is unique when compared with other C. sativa varieties. Georg Thieme Verlag KG Stuttgart · New York.

1H NMR metabolomics of earthworm exposure to sub-lethal concentrations of phenanthrene in soil

International Nuclear Information System (INIS)

Brown, Sarah A.E.; McKelvie, Jennifer R.; Simpson, Andre J.; Simpson, Myrna J.

2010-01-01

1 H NMR metabolomics was used to monitor earthworm responses to sub-lethal (50-1500 mg/kg) phenanthrene exposure in soil. Total phenanthrene was analyzed via soxhlet extraction, bioavailable phenanthrene was estimated by hydroxypropyl-β-cyclodextrin (HPCD) and 1-butanol extractions and sorption to soil was assessed by batch equilibration. Bioavailable phenanthrene (HPCD-extracted) comprised ∼65-97% of total phenanthrene added to the soil. Principal component analysis (PCA) showed differences in responses between exposed earthworms and controls after 48 h exposure. The metabolites that varied with exposure included amino acids (isoleucine, alanine and glutamine) and maltose. PLS models indicated that earthworm response is positively correlated to both total phenanthrene concentration and bioavailable (HPCD-extracted) phenanthrene in a freshly spiked, unaged soil. These results show that metabolomics is a powerful, direct technique that may be used to monitor contaminant bioavailability and toxicity of sub-lethal concentrations of contaminants in the environment. These initial findings warrant further metabolomic studies with aged contaminated soils. - 1 H NMR metabolomics is used to directly monitor metabolic responses of Eisenia fetida after 48 h of exposure to sub-lethal concentrations of phenanthrene in soil.

Metabolomics

DEFF Research Database (Denmark)

Kamstrup-Nielsen, Maja Hermann

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

{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.

NMR-based pharmacometabonomics: A new paradigm for personalised or precision medicine

OpenAIRE

Everett, Jeremy R.

2017-01-01

Metabolic profiling by NMR spectroscopy or hyphenated mass spectrometry, known as metabonomics or metabolomics, is an important tool for systems-based approaches in biology and medicine. The experiments are typically done in a diagnostic fashion where changes in metabolite profiles are interpreted as a consequence of an intervention or event; be that a change in diet, the administration of a drug, physical exertion or the onset of a disease. By contrast, pharmacometabonomics takes a prognosti...

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.

Toxicological effects of cinnabar in rats by NMR-based metabolic profiling of urine and serum

International Nuclear Information System (INIS)

Wei Lai; Liao Peiqiu; Wu Huifeng; Li Xiaojing; Pei Fengkui; Li Weisheng; Wu Yijie

2008-01-01

Cinnabar, an important traditional Chinese mineral medicine, has been widely used as a Chinese patent medicine ingredient for sedative therapy. However, the pharmaceutical and toxicological effects of cinnabar, especially in the whole organism, were subjected to few investigations. In this study, an NMR-based metabolomics approach has been applied to investigate the toxicological effects of cinnabar after intragastrical administration (dosed at 0.5, 2 and 5 g/kg body weight) on male Wistar rats. Liver and kidney histopathology examinations and serum clinical chemistry analyses were also performed. The 1 H NMR spectra were analyzed using multivariate pattern recognition techniques to show the time- and dose-dependent biochemical variations induced by cinnabar. The metabolic signature of urinalysis from cinnabar-treated animals exhibited an increase in the levels of creatinine, acetate, acetoacetate, taurine, hippurate and phenylacetylglycine, together with a decrease in the levels of trimethyl-N-oxide, dimethylglycine and Kreb's cycle intermediates (citrate, 2-oxoglutarate and succinate). The metabolomics analyses of serum showed elevated concentrations of ketone bodies (3-D-hydroxybutyrate and acetoacetate), branched-chain amino acids (valine, leucine and isoleucine), choline and creatine as well as decreased glucose, lipids and lipoproteins from cinnabar-treated animals. These findings indicated cinnabar induced disturbance in energy metabolism, amino acid metabolism and gut microflora environment as well as slight injury in liver and kidney, which might indirectly result from cinnabar induced oxidative stress. This work illustrated the high reliability of NMR-based metabolomic approach on the study of the biochemical effects induced by traditional Chinese medicine

Use of NMR metabolomic plasma profiling methodologies to identify illicit growth-promoting administrations

NARCIS (Netherlands)

Graham, S.F.; Ruiz Aracama, A.; Lommen, A.; Cannizzo, F.T.; Biolatti, B.; Elliott, C.T.; Mooney, M.H.

2012-01-01

Detection of growth-promoter use in animal production systems still proves to be an analytical challenge despite years of activity in the field. This study reports on the capability of NMR metabolomic profiling techniques to discriminate between plasma samples obtained from cattle treated with

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...

{sup 1}H NMR metabolomics of earthworm exposure to sub-lethal concentrations of phenanthrene in soil

Energy Technology Data Exchange (ETDEWEB)

Brown, Sarah A.E.; McKelvie, Jennifer R.; Simpson, Andre J. [Department of Physical and Environmental Sciences, University of Toronto, 1265 Military Trail Toronto, Ontario, M1C 1A4 (Canada); Simpson, Myrna J., E-mail: myrna.simpson@utoronto.c [Department of Physical and Environmental Sciences, University of Toronto, 1265 Military Trail Toronto, Ontario, M1C 1A4 (Canada)

2010-06-15

{sup 1}H NMR metabolomics was used to monitor earthworm responses to sub-lethal (50-1500 mg/kg) phenanthrene exposure in soil. Total phenanthrene was analyzed via soxhlet extraction, bioavailable phenanthrene was estimated by hydroxypropyl-beta-cyclodextrin (HPCD) and 1-butanol extractions and sorption to soil was assessed by batch equilibration. Bioavailable phenanthrene (HPCD-extracted) comprised approx65-97% of total phenanthrene added to the soil. Principal component analysis (PCA) showed differences in responses between exposed earthworms and controls after 48 h exposure. The metabolites that varied with exposure included amino acids (isoleucine, alanine and glutamine) and maltose. PLS models indicated that earthworm response is positively correlated to both total phenanthrene concentration and bioavailable (HPCD-extracted) phenanthrene in a freshly spiked, unaged soil. These results show that metabolomics is a powerful, direct technique that may be used to monitor contaminant bioavailability and toxicity of sub-lethal concentrations of contaminants in the environment. These initial findings warrant further metabolomic studies with aged contaminated soils. - {sup 1}H NMR metabolomics is used to directly monitor metabolic responses of Eisenia fetida after 48 h of exposure to sub-lethal concentrations of phenanthrene in soil.

nmrML: A Community Supported Open Data Standard for the Description, Storage, and Exchange of NMR Data.

Science.gov (United States)

Schober, Daniel; Jacob, Daniel; Wilson, Michael; Cruz, Joseph A; Marcu, Ana; Grant, Jason R; Moing, Annick; Deborde, Catherine; de Figueiredo, Luis F; Haug, Kenneth; Rocca-Serra, Philippe; Easton, John; Ebbels, Timothy M D; Hao, Jie; Ludwig, Christian; Günther, Ulrich L; Rosato, Antonio; Klein, Matthias S; Lewis, Ian A; Luchinat, Claudio; Jones, Andrew R; Grauslys, Arturas; Larralde, Martin; Yokochi, Masashi; Kobayashi, Naohiro; Porzel, Andrea; Griffin, Julian L; Viant, Mark R; Wishart, David S; Steinbeck, Christoph; Salek, Reza M; Neumann, Steffen

2018-01-02

NMR is a widely used analytical technique with a growing number of repositories available. As a result, demands for a vendor-agnostic, open data format for long-term archiving of NMR data have emerged with the aim to ease and encourage sharing, comparison, and reuse of NMR data. Here we present nmrML, an open XML-based exchange and storage format for NMR spectral data. The nmrML format is intended to be fully compatible with existing NMR data for chemical, biochemical, and metabolomics experiments. nmrML can capture raw NMR data, spectral data acquisition parameters, and where available spectral metadata, such as chemical structures associated with spectral assignments. The nmrML format is compatible with pure-compound NMR data for reference spectral libraries as well as NMR data from complex biomixtures, i.e., metabolomics experiments. To facilitate format conversions, we provide nmrML converters for Bruker, JEOL and Agilent/Varian vendor formats. In addition, easy-to-use Web-based spectral viewing, processing, and spectral assignment tools that read and write nmrML have been developed. Software libraries and Web services for data validation are available for tool developers and end-users. The nmrML format has already been adopted for capturing and disseminating NMR data for small molecules by several open source data processing tools and metabolomics reference spectral libraries, e.g., serving as storage format for the MetaboLights data repository. The nmrML open access data standard has been endorsed by the Metabolomics Standards Initiative (MSI), and we here encourage user participation and feedback to increase usability and make it a successful standard.

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

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

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

Science.gov (United States)

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

2016-10-18

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

NMR-based metabolomic studies on the toxicological effects of cadmium and copper on green mussels Perna viridis

International Nuclear Information System (INIS)

Wu Huifeng; Wang Wenxiong

2010-01-01

Traditional toxicology studies have focused on selected biomarkers to characterize the biological stress induced by metals in marine organisms. In this study, a system biology tool, metabolomics, was applied to the marine mussel Perna viridis to investigate changes in the metabolic profiles of soft tissue as a response to copper (Cu) and cadmium (Cd), both as single metal and as a mixture. The major metabolite changes corresponding to metal exposure are related to amino acids, osmolytes, and energy metabolites. Following metal exposure for 1 week, there was a significant increase in the levels of branched chain amino acids, histidine, glutamate, glutamine, hypotaurine, dimethylglycine, arginine and ATP/ADP. For the Cu + Cd co-exposed mussels, the levels of lactate, branched chain amino acid, succinate, and NAD increased, whereas the levels of glucose, glycogen, and ATP/ADP decreased, indicating a different metabolic profile for the single metal exposure groups. After 2 weeks of exposure, the mussels showed acclimatization to Cd exposure based on the recovery of some metabolites. However, the metabolic profile induced by the metal mixture was very similar to that from Cu exposure, suggesting that Cu dominantly induced the metabolic disturbances. Both Cu and Cd may lead to neurotoxicity, disturbances in energy metabolism, and osmoregulation changes. These results demonstrate the high applicability and reliability of NMR-based metabolomics in interpreting the toxicological mechanisms of metals using global metabolic biomarkers.

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

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

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

Directory of Open Access Journals (Sweden)

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.

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)

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.

Insights into the mechanisms underlying mercury-induced oxidative stress in gills of wild fish (Liza aurata) combining "1H NMR metabolomics and conventional biochemical assays

International Nuclear Information System (INIS)

Cappello, Tiziana; Brandão, Fátima; Guilherme, Sofia; Santos, Maria Ana; Maisano, Maria; Mauceri, Angela; Canário, João; Pacheco, Mário; Pereira, Patrícia

2016-01-01

be sensitive and effective towards a mechanistically based assessment of Hg toxicity in gills of wild fish, providing new insights into the toxicological pathways underlying the oxidative stress. - Highlights: • Mercury-induced oxidative stress was investigated in gills of wild fish Liza aurata. • "1H NMR-based metabolomics and oxidative stress biomarkers were applied. • Hg interfered with the antioxidant protection but lipid peroxidation was prevented. • Activation of membrane repair processes suggested cell membrane ability to recover. • The combined approach is a sensitive and effective tool in ecotoxicological studies.

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

Science.gov (United States)

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

2015-08-01

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

1H NMR-based spectroscopy detects metabolic alterations in serum of patients with early-stage ulcerative colitis

International Nuclear Information System (INIS)

Zhang, Ying; Lin, Lianjie; Xu, Yanbin; Lin, Yan; Jin, Yu; Zheng, Changqing

2013-01-01

Highlights: •Twenty ulcerative colitis patients and nineteen healthy controls were enrolled. •Increased 3-hydroxybutyrate, glucose, phenylalanine, and decreased lipid were found. •We report early stage diagnosis of ulcerative colitis using NMR-based metabolomics. -- Abstract: Ulcerative colitis (UC) has seriously impaired the health of citizens. Accurate diagnosis of UC at an early stage is crucial to improve the efficiency of treatment and prognosis. In this study, proton nuclear magnetic resonance ( 1 H NMR)-based metabolomic analysis was performed on serum samples collected from active UC patients (n = 20) and healthy controls (n = 19), respectively. The obtained spectral profiles were subjected to multivariate data analysis. Our results showed that consistent metabolic alterations were present between the two groups. Compared to healthy controls, UC patients displayed increased 3-hydroxybutyrate, β-glucose, α-glucose, and phenylalanine, but decreased lipid in serum. These findings highlight the possibilities of NMR-based metabolomics as a non-invasive diagnostic tool for UC

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

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

Science.gov (United States)

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

2017-12-01

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

NMR metabolomics of human lung tumours reveals distinct metabolic signatures for adenocarcinoma and squamous cell carcinoma

OpenAIRE

Rocha, CM; Barros, AS; Goodfellow, BJ; Carreira, IM; Gomes, AA; Sousa, V; Bernardo, J; Carvalho, L; Gil, AM; Duarte, IF

2015-01-01

Lung tumour subtyping, particularly the distinction between adenocarcinoma (AdC) and squamous cell carcinoma (SqCC), is a critical diagnostic requirement. In this work, the metabolic signatures of lung carcinomas were investigated through (1)H NMR metabolomics, with a view to provide additional criteria for improved diagnosis and treatment planning. High Resolution Magic Angle Spinning Nuclear Magnetic Resonance (NMR) spectroscopy was used to analyse matched tumour and adjacent control tissue...

Protein catabolism and high lipid metabolism associated with long-distance exercise are revealed by plasma NMR metabolomics in endurance horses.

Directory of Open Access Journals (Sweden)

Laurence Le Moyec

Full Text Available During long distance endurance races, horses undergo high physiological and metabolic stresses. The adaptation processes involve the modulation of the energetic pathways in order to meet the energy demand. The aims were to evaluate the effects of long endurance exercise on the plasma metabolomic profiles and to investigate the relationships with the individual horse performances. The metabolomic profiles of the horses were analyzed using the non-dedicated methodology, NMR spectroscopy and statistical multivariate analysis. The advantage of this method is to investigate several metabolomic pathways at the same time in a single sample. The plasmas were obtained before exercise (BE and post exercise (PE from 69 horses competing in three endurance races at national level (130-160 km. Biochemical assays were also performed on the samples taken at PE. The proton NMR spectra were compared using the supervised orthogonal projection on latent structure method according to several factors. Among these factors, the race location was not significant whereas the effect of the race exercise (sample BE vs PE of same horse was highly discriminating. This result was confirmed by the projection of unpaired samples (only BE or PE sample of different horses. The metabolomic profiles proved that protein, energetic and lipid metabolisms as well as glycoproteins content are highly affected by the long endurance exercise. The BE samples from finisher horses could be discriminated according to the racing speed based on their metabolomic lipid content. The PE samples could be discriminated according to the horse ranking position at the end of the race with lactate as unique correlated metabolite. As a conclusion, the metabolomic profiles of plasmas taken before and after the race provided a better understanding of the high energy demand and protein catabolism pathway that could expose the horses to metabolic disorders.

Metabolic effects of dinoseb, diazinon and esfenvalerate in eyed eggs and alevins of Chinook salmon (Oncorhynchus tshawytscha) determined by 1H NMR metabolomics

International Nuclear Information System (INIS)

Viant, Mark R.; Pincetich, Christopher A.; Tjeerdema, Ronald S.

2006-01-01

Pesticide pulses in the Sacramento River, California, originate from storm-water discharges and non-point source aquatic pollution that can last from a few days to weeks. The Sacramento River and its tributaries have historically supported the majority of California's Chinook salmon (Oncorhynchus tshawytscha) spawning grounds. Three pesticides currently used in the Sacramento Valley - dinoseb, diazinon, and esfenvalerate - were chosen to model the exposure of salmon embryos to storm-water discharges. Static-renewal (96 h) exposures to eyed eggs and alevins resulted in both toxicity and significant changes in metabolism assessed in whole-embryo extracts by 1 H nuclear magnetic resonance (NMR) spectroscopy based metabolomics and HPLC with UV detection (HPLC-UV). The 96-h LC 5 values of eyed eggs and alevins exposed to dinoseb were 335 and 70.6 ppb, respectively, and the corresponding values for diazinon were 545 and 29.5 ppm for eyed eggs and alevins, respectively. The 96-h LC 5 of eyed eggs exposed to esfenvalerate could not be determined due to lack of mortality at the highest exposure concentration, but in alevins was 16.7 ppb. All esfenvalerate exposed alevins developed some degree of lordosis or myoskeletal abnormality and did not respond to stimulus or exhibit normal swimming behavior. ATP concentrations measured by HPLC-UV decreased significantly in eyed eggs due to 250 ppb dinoseb and 10 and 100 ppb esfenvalerate (p 1 H NMR metabolite fingerprints of eyed egg and alevin extracts revealed both dose-dependent and mechanism of action-specific metabolic effects induced by the pesticides. Furthermore, NMR based metabolomics proved to be more sensitive than HPLC-UV in identifying significant changes in sublethal metabolism of pesticide exposed alevins. In conclusion, we have demonstrated several benefits of a metabolomics approach for chemical risk assessment, when used in conjunction with a fish embryo assay, and have identified significant metabolic perturbations

Insights into the mechanisms underlying mercury-induced oxidative stress in gills of wild fish (Liza aurata) combining {sup 1}H NMR metabolomics and conventional biochemical assays

Energy Technology Data Exchange (ETDEWEB)

Cappello, Tiziana, E-mail: tcappello@unime.it [Department of Biological and Environmental Sciences, University of Messina, 98166 Messina (Italy); Brandão, Fátima, E-mail: fatimabrandao@ua.pt [Department of Biology and CESAM, University of Aveiro, 3810-193 Aveiro (Portugal); Guilherme, Sofia; Santos, Maria Ana [Department of Biology and CESAM, University of Aveiro, 3810-193 Aveiro (Portugal); Maisano, Maria; Mauceri, Angela [Department of Biological and Environmental Sciences, University of Messina, 98166 Messina (Italy); Canário, João [Centro de Química Estrutural, Instítuto Superíor Técnico, Universidade de Lisboa, 1049-001 Lisbon (Portugal); Pacheco, Mário; Pereira, Patrícia [Department of Biology and CESAM, University of Aveiro, 3810-193 Aveiro (Portugal)

2016-04-01

be sensitive and effective towards a mechanistically based assessment of Hg toxicity in gills of wild fish, providing new insights into the toxicological pathways underlying the oxidative stress. - Highlights: • Mercury-induced oxidative stress was investigated in gills of wild fish Liza aurata. • {sup 1}H NMR-based metabolomics and oxidative stress biomarkers were applied. • Hg interfered with the antioxidant protection but lipid peroxidation was prevented. • Activation of membrane repair processes suggested cell membrane ability to recover. • The combined approach is a sensitive and effective tool in ecotoxicological studies.

Application of NMR-based metabolomics to the study of gut microbiota in obesity.

Science.gov (United States)

Calvani, Riccardo; Brasili, Elisa; Praticò, Giulia; Sciubba, Fabio; Roselli, Marianna; Finamore, Alberto; Marini, Federico; Marzetti, Emanuele; Miccheli, Alfredo

2014-01-01

Lifestyle habits, host gene repertoire, and alterations in the intestinal microbiota concur to the development of obesity. A great deal of research has recently been focused on investigating the role gut microbiota plays in the pathogenesis of metabolic dysfunctions and increased adiposity. Altered microbiota can affect host physiology through several pathways, including enhanced energy harvest, and perturbations in immunity, metabolic signaling, and inflammatory pathways. A broad range of "omics" technologies is now available to help decipher the interactions between the host and the gut microbiota at detailed genetic and functional levels. In particular, metabolomics--the comprehensive analysis of metabolite composition of biological fluids and tissues--could provide breakthrough insights into the links among the gut microbiota, host genetic repertoire, and diet during the development and progression of obesity. Here, we briefly review the most insightful findings on the involvement of gut microbiota in the pathogenesis of obesity. We also discuss how metabolomic approaches based on nuclear magnetic resonance spectroscopy could help understand the activity of gut microbiota in relation to obesity, and assess the effects of gut microbiota modulation in the treatment of this condition.

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

Science.gov (United States)

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

2017-08-05

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

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

DEFF Research Database (Denmark)

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

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

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

Science.gov (United States)

Sud, Manish; Fahy, Eoin; Cotter, Dawn; Azam, Kenan; Vadivelu, Ilango; Burant, Charles; Edison, Arthur; Fiehn, Oliver; Higashi, Richard; Nair, K Sreekumaran; Sumner, Susan; Subramaniam, Shankar

2016-01-04

The Metabolomics Workbench, available at www.metabolomicsworkbench.org, is a public repository for metabolomics metadata and experimental data spanning various species and experimental platforms, metabolite standards, metabolite structures, protocols, tutorials, and training material and other educational resources. It provides a computational platform to integrate, analyze, track, deposit and disseminate large volumes of heterogeneous data from a wide variety of metabolomics studies including mass spectrometry (MS) and nuclear magnetic resonance spectrometry (NMR) data spanning over 20 different species covering all the major taxonomic categories including humans and other mammals, plants, insects, invertebrates and microorganisms. Additionally, a number of protocols are provided for a range of metabolite classes, sample types, and both MS and NMR-based studies, along with a metabolite structure database. The metabolites characterized in the studies available on the Metabolomics Workbench are linked to chemical structures in the metabolite structure database to facilitate comparative analysis across studies. The Metabolomics Workbench, part of the data coordinating effort of the National Institute of Health (NIH) Common Fund's Metabolomics Program, provides data from the Common Fund's Metabolomics Resource Cores, metabolite standards, and analysis tools to the wider metabolomics community and seeks data depositions from metabolomics researchers across the world. © The Author(s) 2015. Published by Oxford University Press on behalf of Nucleic Acids Research.

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.

Mathematical Modeling Approaches in Plant Metabolomics.

Science.gov (United States)

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

2018-01-01

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

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

Science.gov (United States)

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

2015-04-03

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

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

DEFF Research Database (Denmark)

Zheng, Hong; Lorenzen, J.K.; Astrup, A.

2016-01-01

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...... 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...

NMR spectrometers as "magnetic tongues": prediction of sensory descriptors in canned tomatoes

DEFF Research Database (Denmark)

Malmendal, Anders; Amoresano, Claudia; Trotta, Roberta

2011-01-01

The perception of odor and flavor of food is a complicated physiological and psychological process that cannot be explained by simple models. Quantitative descriptive analysis is a technique used to describe sensory features. Nevertheless, the availability of a number of instrumental techniques has...... opened up the possibility to calibrate the sensory perception. In this frame, we have tested the potentiality of nuclear magnetic resonance spectroscopy as a predictive tool to measure sensory descriptors. In particular, we have used an NMR metabolomic approach that allowed us to differentiate...... the analyzed samples based on their chemical composition. We were able to correlate the NMR metabolomic fingerprints recorded for canned tomato samples to the sensory descriptors bitterness, sweetness, sourness, saltiness, tomato and metal taste, redness, and density, suggesting that NMR might be a very useful...

High-Resolution Magic-Angle-Spinning NMR and Magnetic Resonance Imaging Spectroscopies Distinguish Metabolome and Structural Properties of Maize Seeds from Plants Treated with Different Fertilizers and Arbuscular mycorrhizal fungi.

Science.gov (United States)

Mazzei, Pierluigi; Cozzolino, Vincenza; Piccolo, Alessandro

2018-03-21

Both high-resolution magic-angle-spinning (HRMAS) and magnetic resonance imaging (MRI) NMR spectroscopies were applied here to identify the changes of metabolome, morphology, and structural properties induced in seeds (caryopses) of maize plants grown at field level under either mineral or compost fertilization in combination with the inoculation by arbuscular mycorrhizal fungi (AMF). The metabolome of intact caryopses was examined by HRMAS-NMR, while the morphological aspects, endosperm properties and seed water distribution were investigated by MRI. Principal component analysis (PCA) was applied to evaluate 1 H CPMG (Carr-Purcel-Meiboom-Gill) HRMAS spectra as well as several MRI-derived parameters ( T 1 , T 2 , and self-diffusion coefficients) of intact maize caryopses. PCA score-plots from spectral results indicated that both seeds metabolome and structural properties depended on the specific field treatment undergone by maize plants. Our findings show that a combination of multivariate statistical analyses with advanced and nondestructive NMR techniques, such as HRMAS and MRI, enables the evaluation of the effects induced on maize caryopses by different fertilization and management practices at field level. The spectroscopic approach adopted here may become useful for the objective appraisal of the quality of seeds produced under a sustainable agriculture.

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)

New Methodology for Known Metabolite Identification in Metabonomics/Metabolomics: Topological Metabolite Identification Carbon Efficiency (tMICE).

Science.gov (United States)

Sanchon-Lopez, Beatriz; Everett, Jeremy R

2016-09-02

A new, simple-to-implement and quantitative approach to assessing the confidence in NMR-based identification of known metabolites is introduced. The approach is based on a topological analysis of metabolite identification information available from NMR spectroscopy studies and is a development of the metabolite identification carbon efficiency (MICE) method. New topological metabolite identification indices are introduced, analyzed, and proposed for general use, including topological metabolite identification carbon efficiency (tMICE). Because known metabolite identification is one of the key bottlenecks in either NMR-spectroscopy- or mass spectrometry-based metabonomics/metabolomics studies, and given the fact that there is no current consensus on how to assess metabolite identification confidence, it is hoped that these new approaches and the topological indices will find utility.

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.

Informatics for Metabolomics.

Science.gov (United States)

Kusonmano, Kanthida; Vongsangnak, Wanwipa; Chumnanpuen, Pramote

2016-01-01

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

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

NSAIDs can be screened in the preclinical stage of drug development using a NMR based metabolomics approach.

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.

Metabolic effects of dinoseb, diazinon and esfenvalerate in eyed eggs and alevins of Chinook salmon (Oncorhynchus tshawytscha) determined by {sup 1}H NMR metabolomics

Energy Technology Data Exchange (ETDEWEB)

Viant, Mark R [School of Biosciences, The University of Birmingham, Edgbaston, Birmingham, B15 2TT (United Kingdom); Pincetich, Christopher A [Department of Environmental Toxicology, College of Agricultural and Environmental Sciences, University of California, One Shields Avenue, Davis, CA 95616-8588 (United States); Tjeerdema, Ronald S [Department of Environmental Toxicology, College of Agricultural and Environmental Sciences, University of California, One Shields Avenue, Davis, CA 95616-8588 (United States)

2006-05-25

Pesticide pulses in the Sacramento River, California, originate from storm-water discharges and non-point source aquatic pollution that can last from a few days to weeks. The Sacramento River and its tributaries have historically supported the majority of California's Chinook salmon (Oncorhynchus tshawytscha) spawning grounds. Three pesticides currently used in the Sacramento Valley - dinoseb, diazinon, and esfenvalerate - were chosen to model the exposure of salmon embryos to storm-water discharges. Static-renewal (96 h) exposures to eyed eggs and alevins resulted in both toxicity and significant changes in metabolism assessed in whole-embryo extracts by {sup 1}H nuclear magnetic resonance (NMR) spectroscopy based metabolomics and HPLC with UV detection (HPLC-UV). The 96-h LC{sub 5} values of eyed eggs and alevins exposed to dinoseb were 335 and 70.6 ppb, respectively, and the corresponding values for diazinon were 545 and 29.5 ppm for eyed eggs and alevins, respectively. The 96-h LC{sub 5} of eyed eggs exposed to esfenvalerate could not be determined due to lack of mortality at the highest exposure concentration, but in alevins was 16.7 ppb. All esfenvalerate exposed alevins developed some degree of lordosis or myoskeletal abnormality and did not respond to stimulus or exhibit normal swimming behavior. ATP concentrations measured by HPLC-UV decreased significantly in eyed eggs due to 250 ppb dinoseb and 10 and 100 ppb esfenvalerate (p < 0.05). Phosphocreatine, as measured by HPLC-UV, decreased significantly in eyed eggs due to 250 ppb dinoseb, 10 and 100 ppb esfenvalerate, and 100 ppm diazinon (p < 0.05). Principal components analyses of {sup 1}H NMR metabolite fingerprints of eyed egg and alevin extracts revealed both dose-dependent and mechanism of action-specific metabolic effects induced by the pesticides. Furthermore, NMR based metabolomics proved to be more sensitive than HPLC-UV in identifying significant changes in sublethal metabolism of pesticide

Metabolic effects of dinoseb, diazinon and esfenvalerate in eyed eggs and alevins of Chinook salmon (Oncorhynchus tshawytscha) determined by {sup 1}H NMR metabolomics

Energy Technology Data Exchange (ETDEWEB)

Viant, Mark R. [School of Biosciences, The University of Birmingham, Edgbaston, Birmingham, B15 2TT (United Kingdom)]. E-mail: M.Viant@bham.ac.uk; Pincetich, Christopher A. [Department of Environmental Toxicology, College of Agricultural and Environmental Sciences, University of California, One Shields Avenue, Davis, CA 95616-8588 (United States); Tjeerdema, Ronald S. [Department of Environmental Toxicology, College of Agricultural and Environmental Sciences, University of California, One Shields Avenue, Davis, CA 95616-8588 (United States)

2006-05-25

Pesticide pulses in the Sacramento River, California, originate from storm-water discharges and non-point source aquatic pollution that can last from a few days to weeks. The Sacramento River and its tributaries have historically supported the majority of California's Chinook salmon (Oncorhynchus tshawytscha) spawning grounds. Three pesticides currently used in the Sacramento Valley - dinoseb, diazinon, and esfenvalerate - were chosen to model the exposure of salmon embryos to storm-water discharges. Static-renewal (96 h) exposures to eyed eggs and alevins resulted in both toxicity and significant changes in metabolism assessed in whole-embryo extracts by {sup 1}H nuclear magnetic resonance (NMR) spectroscopy based metabolomics and HPLC with UV detection (HPLC-UV). The 96-h LC{sub 5} values of eyed eggs and alevins exposed to dinoseb were 335 and 70.6 ppb, respectively, and the corresponding values for diazinon were 545 and 29.5 ppm for eyed eggs and alevins, respectively. The 96-h LC{sub 5} of eyed eggs exposed to esfenvalerate could not be determined due to lack of mortality at the highest exposure concentration, but in alevins was 16.7 ppb. All esfenvalerate exposed alevins developed some degree of lordosis or myoskeletal abnormality and did not respond to stimulus or exhibit normal swimming behavior. ATP concentrations measured by HPLC-UV decreased significantly in eyed eggs due to 250 ppb dinoseb and 10 and 100 ppb esfenvalerate (p < 0.05). Phosphocreatine, as measured by HPLC-UV, decreased significantly in eyed eggs due to 250 ppb dinoseb, 10 and 100 ppb esfenvalerate, and 100 ppm diazinon (p < 0.05). Principal components analyses of {sup 1}H NMR metabolite fingerprints of eyed egg and alevin extracts revealed both dose-dependent and mechanism of action-specific metabolic effects induced by the pesticides. Furthermore, NMR based metabolomics proved to be more sensitive than HPLC-UV in identifying significant changes in sublethal metabolism of pesticide

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

DEFF Research Database (Denmark)

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

2010-01-01

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

Mass spectrometric based approaches in urine metabolomics and biomarker discovery.

Science.gov (United States)

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

2017-03-01

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

The omics era: what can nuclear magnetic resonance tell us on metabolomics?

Directory of Open Access Journals (Sweden)

Franca Castiglione

2018-02-01

Full Text Available A brief overview of the potentiality and use of the metabolic fingerprint of a system or biological process is here proposed. The information on the type, quantity and variation of the pool of metabolites and its relationship with a given biological process is commonly referred to as metabolomics. One powerful analytical approach to the detection and quantitation of metabolites is by Nuclear Magnetic Resonance Spectroscopy (NMR. Additionally, the recently introduced High Resolution Magic Angle Spinning (HR-MAS NMR approach improved dramatically the potentiality of the method allowing direct sampling of ex vivo specimens, such as tissues and cells, without any pre-treatment or extraction steps. The NMR data can be processed towards the target or non-target analysis of the metabolites. The former passes through the identification of all the metabolites, the latter adopts a multivariate statistical approach such as Principal Components Analysis. In this article, the main methodological points of NMR analysis with multivariate statistics are briefly outlined and discussed. A final case-study on the discrimination of healthy and neoplastic tissues via HR-MAS NMR metabolomics is reported as a paradigmatic application.

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

Directory of Open Access Journals (Sweden)

Guangmang Liu

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

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

DEFF Research Database (Denmark)

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

2015-01-01

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

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

International Nuclear Information System (INIS)

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

2014-01-01

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

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

Science.gov (United States)

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

2018-01-01

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

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.

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

International Nuclear Information System (INIS)

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

2017-01-01

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

mzML2ISA & nmrML2ISA: generating enriched ISA-Tab metadata files from metabolomics XML data.

Science.gov (United States)

Larralde, Martin; Lawson, Thomas N; Weber, Ralf J M; Moreno, Pablo; Haug, Kenneth; Rocca-Serra, Philippe; Viant, Mark R; Steinbeck, Christoph; Salek, Reza M

2017-08-15

Submission to the MetaboLights repository for metabolomics data currently places the burden of reporting instrument and acquisition parameters in ISA-Tab format on users, who have to do it manually, a process that is time consuming and prone to user input error. Since the large majority of these parameters are embedded in instrument raw data files, an opportunity exists to capture this metadata more accurately. Here we report a set of Python packages that can automatically generate ISA-Tab metadata file stubs from raw XML metabolomics data files. The parsing packages are separated into mzML2ISA (encompassing mzML and imzML formats) and nmrML2ISA (nmrML format only). Overall, the use of mzML2ISA & nmrML2ISA reduces the time needed to capture metadata substantially (capturing 90% of metadata on assay and sample levels), is much less prone to user input errors, improves compliance with minimum information reporting guidelines and facilitates more finely grained data exploration and querying of datasets. mzML2ISA & nmrML2ISA are available under version 3 of the GNU General Public Licence at https://github.com/ISA-tools. Documentation is available from http://2isa.readthedocs.io/en/latest/. reza.salek@ebi.ac.uk or isatools@googlegroups.com. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

1H NMR-based metabolomic fingerprinting to determine metabolite levels in serrano peppers (Capsicum annum L.) grown in two different regions.

Science.gov (United States)

Becerra-Martínez, Elvia; Florentino-Ramos, Elideth; Pérez-Hernández, Nury; Gerardo Zepeda-Vallejo, L; Villa-Ruano, Nemesio; Velázquez-Ponce, Manuel; García-Mendoza, Felipe; Bañuelos-Hernández, Angel E

2017-12-01

Chili pepper (Capsicum annuum) is the most important and emblematic condiment in Mexican food. Serrano pepper is a variety of C. annuum that is traditionally cultivated in Mexico and commercialized in local markets. The aim of this study was to describe the 1 H NMR metabolomic profiling of the aqueous phase of serrano peppers harvested from two distinct regions, in the states of Veracruz and Oaxaca, Mexico. According to the current results, aspartate citrate, lactate, leucine and sucrose were found at higher amount in the serrano peppers from Veracruz. On the other hand, acetate, formate, fumarate, malonate, phosphocholine, pyruvate and succinate showed the highest abundance in this product from Oaxaca. These are the main metabolites that distinguish one group from the other. The spectrometric method reported presently is characterized by great simplicity, robustness and reproducibility. Thus, this technique can be used for establishing reliable metabolomic fingerprints of serrano peppers grown under different environmental conditions. Copyright © 2017 Elsevier Ltd. All rights reserved.

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

Proteomic and metabolomic approaches to biomarker discovery

CERN Document Server

Issaq, Haleem J

2013-01-01

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

Metabolic responses of the isopod Porcellionides pruinosus to nickel exposure assessed by (1)H NMR metabolomics.

Science.gov (United States)

Ferreira, Nuno G C; Saborano, Raquel; Morgado, Rui; Cardoso, Diogo N; Rocha, Cláudia M; Soares, Amadeu M V M; Loureiro, Susana; Duarte, Iola F

2016-03-30

This work aimed at characterizing the metabolome of the isopod Porcellionides pruinosus and at assessing its variations over 14 days under laboratory culture conditions and upon exposure to the contaminant metal Nickel (Ni). The spectral profiles obtained by (1)H NMR spectroscopy were thoroughly assigned and subjected to multivariate analysis in order to highlight consistent changes. Over 50 metabolites could be identified, providing considerable new knowledge on the metabolome of these model organisms. Several metabolites changed non-linearly with Ni dose and exposure time, showing distinct variation patterns for initial (4 days) and later time points (7 and 14 days). In particular, at day 4, several amino acids were increased and sugars were decreased (compared to controls), whereas these variations were inverted for longer exposure, possibly reflecting earlier and more intensive moulting. Other variations, namely in betaines and choline-containing compounds, were suggested to relate with osmoregulation and detoxification mechanisms. Ni also had a marked effect on several nucleotides (increased upon exposure) and a moderate impact on lipids (decreased upon exposure). Overall, this study has provided new information on the Ni-induced metabolic adaptations of the P. pruinosus isopod, paving the way for improved mechanistic understanding of how these model organisms handle soil contamination. This study provided, for the first time to our knowledge, a detailed picture of the NMR-detectable metabolome of terrestrial isopods and of its fluctuations in time and upon exposure to the contaminant metal Nickel. Several time- and dose-dependent changes were highlighted, providing mechanistic insight into how these important model organisms handle Ni contamination.

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

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…

Leucine-rich diet alters the 1H-NMR based metabolomic profile without changing the Walker-256 tumour mass in rats.

Science.gov (United States)

Viana, Laís Rosa; Canevarolo, Rafael; Luiz, Anna Caroline Perina; Soares, Raquel Frias; Lubaczeuski, Camila; Zeri, Ana Carolina de Mattos; Gomes-Marcondes, Maria Cristina Cintra

2016-10-03

Cachexia is one of the most important causes of cancer-related death. Supplementation with branched-chain amino acids, particularly leucine, has been used to minimise loss of muscle tissue, although few studies have examined the effect of this type of nutritional supplementation on the metabolism of the tumour-bearing host. Therefore, the present study evaluated whether a leucine-rich diet affects metabolomic derangements in serum and tumour tissues in tumour-bearing Walker-256 rats (providing an experimental model of cachexia). After 21 days feeding Wistar female rats a leucine-rich diet, distributed in L-leucine and LW-leucine Walker-256 tumour-bearing groups, we examined the metabolomic profile of serum and tumour tissue samples and compared them with samples from tumour-bearing rats fed a normal protein diet (C - control; W - tumour-bearing groups). We utilised 1 H-NMR as a means to study the serum and tumour metabolomic profile, tumour proliferation and tumour protein synthesis pathway. Among the 58 serum metabolites examined, we found that 12 were altered in the tumour-bearing group, reflecting an increase in activity of some metabolic pathways related to energy production, which diverted many nutrients toward tumour growth. Despite displaying increased tumour cell activity (i.e., higher Ki-67 and mTOR expression), there were no differences in tumour mass associated with changes in 23 metabolites (resulting from valine, leucine and isoleucine synthesis and degradation, and from the synthesis and degradation of ketone bodies) in the leucine-tumour group. This result suggests that the majority of nutrients were used for host maintenance. A leucine rich-diet, largely used to prevent skeletal muscle loss, did not affect Walker 256 tumour growth and led to metabolomic alterations that may partially explain the positive effects of leucine for the whole tumour-bearing host.

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

Science.gov (United States)

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

2016-05-30

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

Metabolite Profiling of the Microalgal Diatom Chaetoceros Calcitrans and Correlation with Antioxidant and Nitric Oxide Inhibitory Activities via 1H NMR-Based Metabolomics

Directory of Open Access Journals (Sweden)

Awanis Azizan

2018-05-01

Full Text Available Microalgae are promising candidate resources from marine ecology for health-improving effects. Metabolite profiling of the microalgal diatom, Chaetoceros calcitrans was conducted by using robust metabolomics tools, namely 1H nuclear magnetic resonance (NMR spectroscopy coupled with multivariate data analysis (MVDA. The unsupervised data analysis, using principal component analysis (PCA, resolved the five types of extracts made by solvents ranging from polar to non-polar into five different clusters. Collectively, with various extraction solvents, 11 amino acids, cholesterol, 6 fatty acids, 2 sugars, 1 osmolyte, 6 carotenoids and 2 chlorophyll pigments were identified. The fatty acids and both carotenoid pigments as well as chlorophyll, were observed in the extracts made from medium polar (acetone, chloroform and non-polar (hexane solvents. It is suggested that the compounds were the characteristic markers that influenced the separation between the clusters. Based on partial least square (PLS analysis, fucoxanthin, astaxanthin, violaxanthin, zeaxanthin, canthaxanthin, and lutein displayed strong correlation to 2,2-diphenyl-1-picrylhydrazyl (DPPH free radical scavenging and nitric oxide (NO inhibitory activity. This metabolomics study showed that solvent extractions are one of the main bottlenecks for the maximum recovery of bioactive microalgal compounds and could be a better source of natural antioxidants due to a high value of metabolites.

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.

New tools and resources in metabolomics: 2016-2017.

Science.gov (United States)

Misra, Biswapriya B

2018-04-01

Rapid advances in mass spectrometry (MS) and nuclear magnetic resonance (NMR)-based platforms for metabolomics have led to an upsurge of data every single year. Newer high-throughput platforms, hyphenated technologies, miniaturization, and tool kits in data acquisition efforts in metabolomics have led to additional challenges in metabolomics data pre-processing, analysis, interpretation, and integration. Thanks to the informatics, statistics, and computational community, new resources continue to develop for metabolomics researchers. The purpose of this review is to provide a summary of the metabolomics tools, software, and databases that were developed or improved during 2016-2017, thus, enabling readers, developers, and researchers access to a succinct but thorough list of resources for further improvisation, implementation, and application in due course of time. © 2018 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Computational Approaches for Integrative Analysis of the Metabolome and Microbiome

Directory of Open Access Journals (Sweden)

Jasmine Chong

2017-11-01

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

Relationship between recombinant protein expression and host metabolome as determined by two-dimensional NMR spectroscopy.

Directory of Open Access Journals (Sweden)

Young Kee Chae

Full Text Available Escherichia coli has been the most widely used host to produce large amounts of heterologous proteins. However, given an input plasmid DNA, E. coli may produce soluble protein, produce only inclusion bodies, or yield little or no protein at all. Many efforts have been made to surmount these problems, but most of them have involved time-consuming and labor-intensive trial-and-error. We hypothesized that different metabolomic fingerprints might be associated with different protein production outcomes. If so, then it might be possible to change the expression pattern by manipulating the metabolite environment. As a first step in testing this hypothesis, we probed a subset of the intracellular metabolites by partially labeling it with 13C-glucose. We tested 71 genes and identified 17 metabolites by employing the two-dimensional NMR spectroscopy. The statistical analysis showed that there existed the metabolite compositions favoring protein production. We hope that this work would help devise a systematic and predictive approach to the recombinant protein production.

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

Magic Angle Spinning NMR Metabolomics

Energy Technology Data Exchange (ETDEWEB)

Zhi Hu, Jian

2016-01-01

Nuclear Magnetic Resonance (NMR) spectroscopy is a non-destructive, quantitative, reproducible, untargeted and unbiased method that requires no or minimal sample preparation, and is one of the leading analytical tools for metabonomics research [1-3]. The easy quantification and the no need of prior knowledge about compounds present in a sample associated with NMR are advantageous over other techniques [1,4]. 1H NMR is especially attractive because protons are present in virtually all metabolites and its NMR sensitivity is high, enabling the simultaneous identification and monitoring of a wide range of low molecular weight metabolites.

Whole Blood Reveals More Metabolic Detail of the Human Metabolome than Serum as Measured by 1H-NMR Spectroscopy: Implications for Sepsis Metabolomics

Science.gov (United States)

Stringer, Kathleen A.; Younger, John G.; McHugh, Cora; Yeomans, Larisa; Finkel, Michael A.; Puskarich, Michael A.; Jones, Alan E.; Trexel, Julie; Karnovsky, Alla

2015-01-01

Serum is a common sample of convenience for metabolomics studies. Its processing time can be lengthy and may result in the loss of metabolites including those of red blood cells (RBC). Unlike serum, whole blood (WB) is quickly processed, minimizing the influence of variable hemolysis while including RBC metabolites. To determine differences between serum and WB metabolomes, both sample types, collected from healthy volunteers, were assayed by 1H-NMR spectroscopy. A total of 34 and 50 aqueous metabolites were quantified from serum and WB, respectively. Free hemoglobin (Hgb) levels in serum were measured and the correlation between Hgb and metabolite concentrations was determined. All metabolites detected in serum were at higher concentrations in WB with the exception of acetoacetate and propylene glycol. The 18 unique metabolites of WB included adenosine, AMP, ADP and ATP, which are associated with RBC metabolism. The use of serum results in the underrepresentation of a number of metabolic pathways including branched chain amino acid degradation and glycolysis and gluconeogenesis. The range of free Hgb in serum was 0.03-0.01 g/dL and 8 metabolites were associated (p ≤ 0.05) with free Hgb. The range of free Hgb in serum samples from 18 sepsis patients was 0.02-0.46 g/dL. WB and serum have unique aqueous metabolite profiles but the use of serum may introduce potential pathway bias. Use of WB for metabolomics may be particularly important for studies in diseases like sepsis in which RBC metabolism is altered and mechanical and sepsis-induced hemolysis contributes to variance in the metabolome. PMID:26009817

Serum 1H-NMR metabolomic fingerprints of acute-on-chronic liver failure in intensive care unit patients with alcoholic cirrhosis.

Directory of Open Access Journals (Sweden)

Roland Amathieu

Full Text Available INTRODUCTION: Acute-on-chronic liver failure is characterized by acute deterioration of liver function in patients with compensated or decompensated, but stable, cirrhosis. However, there is no accurate definition of acute-on-chronic liver failure and physicians often use this term to describe different clinical entities. Metabolomics investigates metabolic changes in biological systems and identifies the biomarkers or metabolic profiles. Our study assessed the metabolomic profile of serum using proton nuclear magnetic resonance ((1H-NMR spectroscopy to identify metabolic changes related to acute-on-chronic liver failure. PATIENTS: Ninety-three patients with compensated or decompensated cirrhosis (CLF group but stable liver function and 30 patients with cirrhosis and hospitalized for the management of an acute event who may be responsible of acute-on-chronic liver failure (ACLF group, were fully analyzed. Blood samples were drawn at admission, and sera were separated and stored at -80°C until (1H-NMR spectral analysis. Using orthogonal projection to latent-structure discriminant analyses, various metabolites contribute to the complete separation between these both groups. RESULTS: The predictability of the model was 0.73 (Q(2 Y and the explained variance was 0.63 (R(2 Y. The main metabolites that had increased signals related to acute-on-chronic liver failure were lactate, pyruvate, ketone bodies, glutamine, phenylalanine, tyrosine, and creatinine. High-density lipids were lower in the ALCF group than in CLF group. CONCLUSION: A serum metabolite fingerprint for acute-on-chronic liver failure, obtained with (1H-NMR, was identified. Metabolomic profiling may aid clinical evaluation of patients with cirrhosis admitted into intensive care units with acute-on-chronic liver failure, and provide new insights into the metabolic processes involved in acute impairment of hepatic function.

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

Metabolomic analyses of fecal material are gaining increasing attention because the gut microbial ecology and activity have an impact on the human phenotype and regulate host metabolism. Sample preparation is a crucial step, and in this study we recommend a methodology for extraction and analysis......, 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...

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

Science.gov (United States)

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

2016-01-01

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

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

Directory of Open Access Journals (Sweden)

Najla Gooda Sahib Jambocus

2016-01-01

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

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

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.

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.

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

DEFF Research Database (Denmark)

Rago, Daniela; Kristensen, Mette; Gürdeniz, Gözde

2013-01-01

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

Environmental metabolomics with data science for investigating ecosystem homeostasis.

Science.gov (United States)

Kikuchi, Jun; Ito, Kengo; Date, Yasuhiro

2018-02-01

A natural ecosystem can be viewed as the interconnections between complex metabolic reactions and environments. Humans, a part of these ecosystems, and their activities strongly affect the environments. To account for human effects within ecosystems, understanding what benefits humans receive by facilitating the maintenance of environmental homeostasis is important. This review describes recent applications of several NMR approaches to the evaluation of environmental homeostasis by metabolic profiling and data science. The basic NMR strategy used to evaluate homeostasis using big data collection is similar to that used in human health studies. Sophisticated metabolomic approaches (metabolic profiling) are widely reported in the literature. Further challenges include the analysis of complex macromolecular structures, and of the compositions and interactions of plant biomass, soil humic substances, and aqueous particulate organic matter. To support the study of these topics, we also discuss sample preparation techniques and solid-state NMR approaches. Because NMR approaches can produce a number of data with high reproducibility and inter-institution compatibility, further analysis of such data using machine learning approaches is often worthwhile. We also describe methods for data pretreatment in solid-state NMR and for environmental feature extraction from heterogeneously-measured spectroscopic data by machine learning approaches. Copyright © 2017. Published by Elsevier B.V.

Identification of anti-HIV active dicaffeoylquinic- and tricaffeoylquinic acids in Helichrysum populifolium by NMR-based metabolomic guided fractionation.

Science.gov (United States)

Heyman, Heino Martin; Senejoux, François; Seibert, Isabell; Klimkait, Thomas; Maharaj, Vinesh Jaichand; Meyer, Jacobus Johannes Marion

2015-06-01

South Africa being home to more than 35% of the world's Helichrysum species (c.a. 244) of which many are used in traditional medicine, is seen potentially as a significant resource in the search of new anti-HIV chemical entities. It was established that five of the 30 Helichrysum species selected for this study had significant anti-HIV activity ranging between 12 and 21 μg/mL (IC50) by using an in-house developed DeCIPhR method on a full virus model. Subsequent toxicity tests also revealed little or no toxicity for these active extracts. With the use of NMR-based metabolomics, the search for common chemical characteristics within the plant extract was conducted, which resulted in specific chemical shift areas identified that could be linked to the anti-HIV activity of the extracts. The NMR chemical shifts associated with the activity were identified to be 2.56-3.08 ppm, 5.24-6.28 ppm, 6.44-7.04 ppm and 7.24-8.04 ppm. This activity profile was then used to guide the fractionation process by narrowing down and focusing the fractionation and purification processes to speed up the putative identification of five compounds with anti-HIV activity in the most active species, Helichrysum populifolium. The anti-HIV compounds identified for the first time from H. populifolium were three dicaffeoylquinic acid derivatives, i.e. 3,4-dicaffeoylquinic acid, 3,5-dicaffeoylquinic acid and 4,5-dicaffeoylquinic acid as well as two tricaffeoylquinic acid derivatives i.e. 1,3,5-tricaffeoylquinic acid and either 5-malonyl-1,3,4-tricaffeoylquinic or 3-malonyl-1,4,5-tricaffeoylquinic acid, with the latter being identified for the first time in the genus. Copyright © 2015 Elsevier B.V. All rights reserved.

Metabolomics of meat exudate: Its potential to evaluate beef meat conservation and aging

International Nuclear Information System (INIS)

Castejón, David; García-Segura, Juan Manuel; Escudero, Rosa; Herrera, Antonio; Cambero, María Isabel

2015-01-01

In this study we analyzed the exudate of beef to evaluate its potential as non invasive sampling for nuclear magnetic resonance (NMR) based metabolomic analysis of meat samples. Exudate, as the natural juice from raw meat, is an easy to obtain matrix that it is usually collected in small amounts in commercial meat packages. Although meat exudate could provide complete and homogeneous metabolic information about the whole meat piece, this sample has been poorly studied. Exudates from 48 beef samples of different breeds, cattle and storage times have been studied by "1H NMR spectroscopy. The liquid exudate spectra were compared with those obtained by High Resolution Magic Angle Spinning (HRMAS) of the original meat pieces. The close correlation found between both spectra (>95% of coincident peaks in both registers; Spearman correlation coefficient = 0.945) lead us to propose the exudate as an excellent alternative analytical matrix with a view to apply meat metabolomics. 60 metabolites could be identified through the analysis of mono and bidimensional exudate spectra, 23 of them for the first time in NMR meat studies. The application of chemometric tools to analyze exudate dataset has revealed significant metabolite variations associated with meat aging. Hence, NMR based metabolomics have made it possible both to classify meat samples according to their storage time through Principal Component Analysis (PCA), and to predict that storage time through Partial Least Squares (PLS) regression. - Highlights: • NMR spectra from beef samples and their exudates are very strongly correlated. • 23 metabolites not reported in previous NMR meat studies have been identified. • Meat exudate NMR spectra allow monitoring of biochemical changes related to aging. • PCA of exudate NMR spectra classified meat samples by their storage time. • The aging of a meat sample can be predicted by PLS analysis of its exudate.

Metabolomics of meat exudate: Its potential to evaluate beef meat conservation and aging

Energy Technology Data Exchange (ETDEWEB)

Castejón, David [Centro de Asistencia a la Investigación de Resonancia Magnética Nuclear y de Espín Electrónico, Universidad Complutense de Madrid, 28040 Madrid (Spain); García-Segura, Juan Manuel [Centro de Asistencia a la Investigación de Resonancia Magnética Nuclear y de Espín Electrónico, Universidad Complutense de Madrid, 28040 Madrid (Spain); Departamento de Bioquímica y Biología Molecular I, Facultad de Químicas, Universidad Complutense de Madrid, 28040 Madrid (Spain); Escudero, Rosa [Departamento de Nutrición, Bromatología y Tecnología de los Alimentos, Facultad de Veterinaria. Universidad Complutense de Madrid, 28040 Madrid (Spain); Herrera, Antonio [Departamento de Química Orgánica, Facultad de Químicas, Universidad Complutense de Madrid, 28040 Madrid (Spain); Cambero, María Isabel, E-mail: icambero@vet.ucm.es [Departamento de Nutrición, Bromatología y Tecnología de los Alimentos, Facultad de Veterinaria. Universidad Complutense de Madrid, 28040 Madrid (Spain)

2015-12-11

In this study we analyzed the exudate of beef to evaluate its potential as non invasive sampling for nuclear magnetic resonance (NMR) based metabolomic analysis of meat samples. Exudate, as the natural juice from raw meat, is an easy to obtain matrix that it is usually collected in small amounts in commercial meat packages. Although meat exudate could provide complete and homogeneous metabolic information about the whole meat piece, this sample has been poorly studied. Exudates from 48 beef samples of different breeds, cattle and storage times have been studied by {sup 1}H NMR spectroscopy. The liquid exudate spectra were compared with those obtained by High Resolution Magic Angle Spinning (HRMAS) of the original meat pieces. The close correlation found between both spectra (>95% of coincident peaks in both registers; Spearman correlation coefficient = 0.945) lead us to propose the exudate as an excellent alternative analytical matrix with a view to apply meat metabolomics. 60 metabolites could be identified through the analysis of mono and bidimensional exudate spectra, 23 of them for the first time in NMR meat studies. The application of chemometric tools to analyze exudate dataset has revealed significant metabolite variations associated with meat aging. Hence, NMR based metabolomics have made it possible both to classify meat samples according to their storage time through Principal Component Analysis (PCA), and to predict that storage time through Partial Least Squares (PLS) regression. - Highlights: • NMR spectra from beef samples and their exudates are very strongly correlated. • 23 metabolites not reported in previous NMR meat studies have been identified. • Meat exudate NMR spectra allow monitoring of biochemical changes related to aging. • PCA of exudate NMR spectra classified meat samples by their storage time. • The aging of a meat sample can be predicted by PLS analysis of its exudate.

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

Science.gov (United States)

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

2015-05-01

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

Multi-platform metabolomics assays for human lung lavage fluids in an air pollution exposure study.

Science.gov (United States)

Surowiec, Izabella; Karimpour, Masoumeh; Gouveia-Figueira, Sandra; Wu, Junfang; Unosson, Jon; Bosson, Jenny A; Blomberg, Anders; Pourazar, Jamshid; Sandström, Thomas; Behndig, Annelie F; Trygg, Johan; Nording, Malin L

2016-07-01

Metabolomics protocols are used to comprehensively characterize the metabolite content of biological samples by exploiting cutting-edge analytical platforms, such as gas chromatography (GC) or liquid chromatography (LC) coupled to mass spectrometry (MS) assays, as well as nuclear magnetic resonance (NMR) assays. We have developed novel sample preparation procedures combined with GC-MS, LC-MS, and NMR metabolomics profiling for analyzing bronchial wash (BW) and bronchoalveolar lavage (BAL) fluid from 15 healthy volunteers following exposure to biodiesel exhaust and filtered air. Our aim was to investigate the responsiveness of metabolite profiles in the human lung to air pollution exposure derived from combustion of biofuels, such as rapeseed methyl ester biodiesel, which are increasingly being promoted as alternatives to conventional fossil fuels. Our multi-platform approach enabled us to detect the greatest number of unique metabolites yet reported in BW and BAL fluid (82 in total). All of the metabolomics assays indicated that the metabolite profiles of the BW and BAL fluids differed appreciably, with 46 metabolites showing significantly different levels in the corresponding lung compartments. Furthermore, the GC-MS assay revealed an effect of biodiesel exhaust exposure on the levels of 1-monostearylglycerol, sucrose, inosine, nonanoic acid, and ethanolamine (in BAL) and pentadecanoic acid (in BW), whereas the LC-MS assay indicated a shift in the levels of niacinamide (in BAL). The NMR assay only identified lactic acid (in BW) as being responsive to biodiesel exhaust exposure. Our findings demonstrate that the proposed multi-platform approach is useful for wide metabolomics screening of BW and BAL fluids and can facilitate elucidation of metabolites responsive to biodiesel exhaust exposure. Graphical Abstract Graphical abstract illustrating the study workflow. NMR Nuclear Magnetic Resonance, LC-TOFMS Liquid chromatography-Time Of Flight Mass Spectrometry, GC Gas

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

Directory of Open Access Journals (Sweden)

Ina Aretz

2016-04-01

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

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

Science.gov (United States)

Aretz, Ina; Meierhofer, David

2016-04-27

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

Identifying biomarkers for asthma diagnosis using targeted metabolomics approaches.

Science.gov (United States)

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

2016-12-01

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

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.

Nuclear magnetic resonance-based serum metabolic profiling of dairy cows with footrot.

Science.gov (United States)

Zheng, Jiasan; Sun, Lingwei; Shu, Shi; Zhu, Kuiling; Xu, Chuang; Wang, Junsong; Wang, Hongbin

2016-10-01

Footrot is a debilitating and contagious disease in dairy cows, caused by the Gram-negative anaerobe Dichelobacter nodosus. 1 H-NMR (nuclear magnetic resonance)-based metabolomics has been previously used to understand the pathology and etiology of several diseases. The objective of this study was to characterize serum from dairy cows with footrot (n=10) using 1 H-NMR-based metabolomics and chemometric analyses. 1 H-NMR spectroscopy with multivariate pattern recognition (principal component analysis and orthogonal partial least-squares discriminant analysis) was performed to identify biomarkers in cows with footrot (F) and healthy controls (C). 1 H-NMR analysis facilitated the identification of 21 metabolites. Among these metabolites, 4 metabolites were higher and 17 metabolites were lower in the F group than in the C group. The serum levels of 5 metabolites were significantly different (Pcows with footrot have altered carbohydrate, amino acid, lipid and energy metabolic pathways. Metabolomic approaches are a clinically useful diagnostic tool for understanding the biochemical alterations and mechanisms of several diseases.

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

Science.gov (United States)

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

2018-02-01

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

Metabolomics, a promising approach to translational research in cardiology

Directory of Open Access Journals (Sweden)

Martino Deidda

2015-12-01

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

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...

The Human Serum Metabolome

Science.gov (United States)

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

2011-01-01

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

Radiation metabolomics : a window to high throughput radiation biodosimetry

International Nuclear Information System (INIS)

Rana, Poonam

2016-01-01

In the event of an intentional or accidental release of ionizing radiation in a densely populated area, timely assessment and triage of the general population for radiation exposure is critical. In particular, a significant number of victims may sustain radiation injury, which increases mortality and worsens the overall prognosis of victims from radiation trauma. Availability of a high-throughput noninvasive in vivo biodosimetry tool for assessing the radiation exposure is of particular importance for timely diagnosis of radiation injury. In this study, we describe the potential NMR techniques in evaluating the radiation injury. NMR is the most versatile technique that has been extensively used in the diverse fields of science since its discovery. NMR and biomedical sciences have been going hand in hand since its application in clinical imaging as MRI and metabolic profiling of biofluids was identified. We have established an NMR based metabonomic and in vivo spectroscopy approach to analyse and identify metabolic profile to measure metabolic fingerprint for radiation exposure. NMR spectroscopy experiments were conducted on urine and serum samples collected from mice irradiated with different doses of radiation. Additionally, in vivo NMR spectroscopy was also performed in different region of brains post irradiation in animal model. A number of metabolites associated with energy metabolism, gut flora metabolites, osmolytes, amino acids and membrane metabolism were identified in serum and urine metabolome. Our results illustrated a metabolic fingerprint for radiation exposure that elucidates perturbed physiological functions. Quantitative as well as multivariate analysis/assessment of these metabolites demonstrated dose and time dependent toxicological effect. In vivo spectroscopy from brain showed radiation induced changes in hippocampus region indicating whole body radiation had striking effect on brain metabolism as well. The results of the present work lay a

Does the 1H-NMR plasma metabolome reflect the host-tumor interactions in human breast cancer?

Science.gov (United States)

Richard, Vincent; Conotte, Raphaël; Mayne, David; Colet, Jean-Marie

2017-07-25

Breast cancer (BC) is the most common diagnosed cancer and the leading cause of cancer death in women worldwide. There is an obvious need for a better understanding of BC biology. Alterations in the serum metabolome of BC patients have been identified but their clinical significance remains elusive. We evaluated by 1H-Nuclear Magnetic Resonance (1H-NMR) spectroscopy, filtered plasma metabolome of 50 early (EBC) and 15 metastatic BC (MBC) patients. Using Principal Component Analysis, Partial Least-Squares Discriminant Analysis and Hierarchical Clustering we show that plasma levels of glucose, lactate, pyruvate, alanine, leucine, isoleucine, glutamate, glutamine, valine, lysine, glycine, threonine, tyrosine, phenylalanine, acetate, acetoacetate, β-hydroxy-butyrate, urea, creatine and creatinine are modulated across patients clusters. In particular lactate levels are inversely correlated with the tumor size in the EBC cohort (Pearson correlation r = -0.309; p = 0.044). We suggest that, in BC patients, tumor cells could induce modulation of the whole patient's metabolism even at early stages. If confirmed in a lager study these observations could be of clinical importance.

Push-through Direction Injectin NMR Automation

Science.gov (United States)

Nuclear magnetic resonance (NMR) and mass spectrometry (MS) are the two major spectroscopic techniques successfully used in metabolomics studies. The non-invasive, quantitative and reproducible characteristics make NMR spectroscopy an excellent technique for detection of endogeno...

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.

Fusion of mass spectrometry-based metabolomics data

NARCIS (Netherlands)

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

2005-01-01

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

Quantitative 1H NMR metabolomics reveals extensive metabolic reprogramming of primary and secondary metabolism in elicitor-treated opium poppy cell cultures

Directory of Open Access Journals (Sweden)

Vogel Hans J

2008-01-01

Full Text Available Abstract Background Opium poppy (Papaver somniferum produces a diverse array of bioactive benzylisoquinoline alkaloids and has emerged as a model system to study plant alkaloid metabolism. The plant is cultivated as the only commercial source of the narcotic analgesics morphine and codeine, but also produces many other alkaloids including the antimicrobial agent sanguinarine. Modulations in plant secondary metabolism as a result of environmental perturbations are often associated with the altered regulation of other metabolic pathways. As a key component of our functional genomics platform for opium poppy we have used proton nuclear magnetic resonance (1H NMR metabolomics to investigate the interplay between primary and secondary metabolism in cultured opium poppy cells treated with a fungal elicitor. Results Metabolite fingerprinting and compound-specific profiling showed the extensive reprogramming of primary metabolic pathways in association with the induction of alkaloid biosynthesis in response to elicitor treatment. Using Chenomx NMR Suite v. 4.6, a software package capable of identifying and quantifying individual compounds based on their respective signature spectra, the levels of 42 diverse metabolites were monitored over a 100-hour time course in control and elicitor-treated opium poppy cell cultures. Overall, detectable and dynamic changes in the metabolome of elicitor-treated cells, especially in cellular pools of carbohydrates, organic acids and non-protein amino acids were detected within 5 hours after elicitor treatment. The metabolome of control cultures also showed substantial modulations 80 hours after the start of the time course, particularly in the levels of amino acids and phospholipid pathway intermediates. Specific flux modulations were detected throughout primary metabolism, including glycolysis, the tricarboxylic acid cycle, nitrogen assimilation, phospholipid/fatty acid synthesis and the shikimate pathway, all of which

Metabolomics with Nuclear Magnetic Resonance Spectroscopy in a Drosophila melanogaster Model of Surviving Sepsis

Science.gov (United States)

Bakalov, Veli; Amathieu, Roland; Triba, Mohamed N.; Clément, Marie-Jeanne; Reyes Uribe, Laura; Le Moyec, Laurence; Kaynar, Ata Murat

2016-01-01

Patients surviving sepsis demonstrate sustained inflammation, which has been associated with long-term complications. One of the main mechanisms behind sustained inflammation is a metabolic switch in parenchymal and immune cells, thus understanding metabolic alterations after sepsis may provide important insights to the pathophysiology of sepsis recovery. In this study, we explored metabolomics in a novel Drosophila melanogaster model of surviving sepsis using Nuclear Magnetic Resonance (NMR), to determine metabolite profiles. We used a model of percutaneous infection in Drosophila melanogaster to mimic sepsis. We had three experimental groups: sepsis survivors (infected with Staphylococcus aureus and treated with oral linezolid), sham (pricked with an aseptic needle), and unmanipulated (positive control). We performed metabolic measurements seven days after sepsis. We then implemented metabolites detected in NMR spectra into the MetExplore web server in order to identify the metabolic pathway alterations in sepsis surviving Drosophila. Our NMR metabolomic approach in a Drosophila model of recovery from sepsis clearly distinguished between all three groups and showed two different metabolomic signatures of inflammation. Sham flies had decreased levels of maltose, alanine, and glutamine, while their level of choline was increased. Sepsis survivors had a metabolic signature characterized by decreased glucose, maltose, tyrosine, beta-alanine, acetate, glutamine, and succinate. PMID:28009836

New Computational Approaches for NMR-based Drug Design: A Protocol for Ligand Docking to Flexible Target Sites

International Nuclear Information System (INIS)

Gracia, Luis; Speidel, Joshua A.; Weinstein, Harel

2006-01-01

NMR-based drug design has met with some success in the last decade, as illustrated in numerous instances by Fesik's ''ligand screening by NMR'' approach. Ongoing efforts to generalize this success have led us to the development of a new paradigm in which quantitative computational approaches are being integrated with NMR derived data and biological assays. The key component of this work is the inclusion of the intrinsic dynamic quality of NMR structures in theoretical models and its use in docking. A new computational protocol is introduced here, designed to dock small molecule ligands to flexible proteins derived from NMR structures. The algorithm makes use of a combination of simulated annealing monte carlo simulations (SA/MC) and a mean field potential informed by the NMR data. The new protocol is illustrated in the context of an ongoing project aimed at developing new selective inhibitors for the PCAF bromodomains that interact with HIV Tat

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

Science.gov (United States)

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

2016-01-07

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

Strategy for NMR metabolomic analysis of urine in mouse models of obesity- from sample collection to interpretation of acquired data

Czech Academy of Sciences Publication Activity Database

Pelantová, Helena; Bugáňová, Martina; Anýž, J.; Železná, Blanka; Maletínská, Lenka; Novák, D.; Haluzík, M.; Kuzma, Marek

2015-01-01

Roč. 115, NOV 10 (2015), s. 225-235 ISSN 0731-7085 R&D Projects: GA ČR GA13-14105S; GA MŠk LO1509 Grant - others:OPPC(XE) CZ.2.16/3.1.00/24023 Institutional support: RVO:61388971 ; RVO:61388963 Keywords : NMR metabolomics * Mouse * Obesity Subject RIV: CB - Analytical Chemistry, Separation; CB - Analytical Chemistry, Separation (UOCHB-X) OBOR OECD: Analytical chemistry; Analytical chemistry (UOCHB-X) Impact factor: 3.169, year: 2015

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

NARCIS (Netherlands)

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

2015-01-01

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

1H NMR-based metabolic profiling reveals inherent biological variation in yeast and nematode model systems

International Nuclear Information System (INIS)

Szeto, Samuel S. W.; Reinke, Stacey N.; Lemire, Bernard D.

2011-01-01

The application of metabolomics to human and animal model systems is poised to provide great insight into our understanding of disease etiology and the metabolic changes that are associated with these conditions. However, metabolomic studies have also revealed that there is significant, inherent biological variation in human samples and even in samples from animal model systems where the animals are housed under carefully controlled conditions. This inherent biological variability is an important consideration for all metabolomics analyses. In this study, we examined the biological variation in 1 H NMR-based metabolic profiling of two model systems, the yeast Saccharomyces cerevisiae and the nematode Caenorhabditis elegans. Using relative standard deviations (RSD) as a measure of variability, our results reveal that both model systems have significant amounts of biological variation. The C. elegans metabolome possesses greater metabolic variance with average RSD values of 29 and 39%, depending on the food source that was used. The S. cerevisiae exometabolome RSD values ranged from 8% to 12% for the four strains examined. We also determined whether biological variation occurs between pairs of phenotypically identical yeast strains. Multivariate statistical analysis allowed us to discriminate between pair members based on their metabolic phenotypes. Our results highlight the variability of the metabolome that exists even for less complex model systems cultured under defined conditions. We also highlight the efficacy of metabolic profiling for defining these subtle metabolic alterations.

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

Science.gov (United States)

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

2015-02-01

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

A functional genomics approach using metabolomics and in silico pathway analysis

DEFF Research Database (Denmark)

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

2002-01-01

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

NMR in structure-based drug design.

Science.gov (United States)

Carneiro, Marta G; Ab, Eiso; Theisgen, Stephan; Siegal, Gregg

2017-11-08

NMR spectroscopy is a powerful technique that can provide valuable structural information for drug discovery endeavors. Here, we discuss the strengths (and limitations) of NMR applications to structure-based drug discovery, highlighting the different levels of resolution and throughput obtainable. Additionally, the emerging field of paramagnetic NMR in drug discovery and recent developments in approaches to speed up and automate protein-observed NMR data collection and analysis are discussed. © 2017 The Author(s). Published by Portland Press Limited on behalf of the Biochemical Society.

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.

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

Science.gov (United States)

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

2011-01-01

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

Two-Phase Extraction for Comprehensive Analysis of the Plant Metabolome by NMR.

Science.gov (United States)

Schripsema, Jan; Dagnino, Denise

2018-01-01

Metabolomics is the area of research, which strives to obtain complete metabolic fingerprints, to detect differences between them, and to provide hypothesis to explain those differences [1]. But obtaining complete metabolic fingerprints is not an easy task. Metabolite extraction is a key step during this process, and much research has been devoted to finding the best solvent mixture to extract as much metabolites as possible.Here a procedure is described for analysis of both polar and apolar metabolites using a two-phase extraction system. D 2 O and CDCl 3 are the solvents of choice, and their major advantage is that, for the identification of the compounds, standard databases can be used because D 2 O and CDCl 3 are the solvents most commonly used for pure compound NMR spectra. The procedure enables the absolute quantification of components via the addition of suitable internal standards. The extracts are also suitable for further analysis with other systems like LC-MS or GC-MS.

Metabolomics reveals energetic impairments in Daphnia magna exposed to diazinon, malathion and bisphenol-A

International Nuclear Information System (INIS)

Nagato, Edward G.; Simpson, André J.; Simpson, Myrna J.

2016-01-01

Highlights: • Metabolomics detected shifts with sub-lethal exposure to contaminants. • Diazinon and malathion induced comparable, non-linear responses. • Bisphenol-A resulted in energy impairment. • Overall, insight into sub-lethal toxicity was garnered using NMR-based metabolomics. - Abstract: "1H nuclear magnetic resonance (NMR)-based metabolomics was used to study the response of Daphnia magna to increasing sub-lethal concentrations of either an organophosphate (diazinon or malathion) or bisphenol-A (BPA). Principal component analysis (PCA) of "1H NMR spectra were used to screen metabolome changes after 48 h of contaminant exposure. The PCA scores plots showed that diazinon exposures resulted in aberrant metabolomic profiles at all exposure concentrations tested (0.009–0.135 μg/L), while for malathion the second lowest (0.08 μg/L) and two highest exposure concentrations (0.32 μg/L and 0.47 μg/L) caused significant shifts from the control. Individual metabolite changes for both organophosphates indicated that the response to increasing exposure was non-linear and described perturbations in the metabolome that were characteristic of the severity of exposure. For example, intermediate concentrations of diazinon (0.045 μg/L and 0.09 μg/L) and malathion (0.08 μg/L) elicited a decrease in amino acids such as leucine, valine, arginine, glycine, lysine, glutamate, glutamine, phenylalanine and tyrosine, with concurrent increases in glucose and lactate, suggesting a mobilization of energy resources to combat stress. At the highest exposure concentrations for both organophosphates there was evidence of a cessation in metabolic activity, where the same amino acids increased and glucose and lactate decreased, suggesting a slowdown in protein synthesis and depletion of energy stocks. This demonstrated a similar response in the metabolome between two organophosphates but also that intermediate and severe stress levels could be differentiated by changes in the

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

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.

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

Evidence of a DHA Signature in the Lipidome and Metabolome of Human Hepatocytes

Directory of Open Access Journals (Sweden)

Veronica Ghini

2017-02-01

Full Text Available Cell supplementation with bioactive molecules often causes a perturbation in the whole intracellular environment. Omics techniques can be applied for the assessment of this perturbation. In this study, the overall effect of docosahexaenoic acid (DHA supplementation on cultured human hepatocyte lipidome and metabolome has been investigated using nuclear magnetic resonance (NMR in combination with traditional techniques. The effect of two additional bioactives sharing with DHA the lipid-lowering effect—propionic acid (PRO and protocatechuic acid (PCA—has also been evaluated in the context of possible synergism. NMR analysis of the cell lipid extracts showed that DHA supplementation, alone or in combination with PCA or PRO, strongly altered the cell lipid profile. The perfect discrimination between cells receiving DHA (alone or in combination and the other cells reinforced the idea of a global rearrangement of the lipid environment induced by DHA. Notably, gas chromatography and fluorimetric analyses confirmed the strong discrimination obtained by NMR. The DHA signature was evidenced not only in the cell lipidome, but also in the metabolome. Results reported herein indicate that NMR, combined with other techniques, represents a fundamental approach to studying the effect of bioactive supplementation, particularly in the case of molecules with a broad spectrum of mechanisms of action.

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

Directory of Open Access Journals (Sweden)

Mohana Krishna Reddy Mudiam

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

Short overview on metabolomic approach and redox changes in psychiatric disorders

Directory of Open Access Journals (Sweden)

Gordana Nedic Erjavec

2018-04-01

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

Recommended strategies for spectral processing and post-processing of 1D 1H-NMR data of biofluids with a particular focus on urine

KAUST Repository

Emwas, Abdul-Hamid M.

2018-02-12

1H NMR spectra from urine can yield information-rich data sets that offer important insights into many biological and biochemical phenomena. However, the quality and utility of these insights can be profoundly affected by how the NMR spectra are processed and interpreted. For instance, if the NMR spectra are incorrectly referenced or inconsistently aligned, the identification of many compounds will be incorrect. If the NMR spectra are mis-phased or if the baseline correction is flawed, the estimated concentrations of many compounds will be systematically biased. Furthermore, because NMR permits the measurement of concentrations spanning up to five orders of magnitude, several problems can arise with data analysis. For instance, signals originating from the most abundant metabolites may prove to be the least biologically relevant while signals arising from the least abundant metabolites may prove to be the most important but hardest to accurately and precisely measure. As a result, a number of data processing techniques such as scaling, transformation and normalization are often required to address these issues. Therefore, proper processing of NMR data is a critical step to correctly extract useful information in any NMR-based metabolomic study. In this review we highlight the significance, advantages and disadvantages of different NMR spectral processing steps that are common to most NMR-based metabolomic studies of urine. These include: chemical shift referencing, phase and baseline correction, spectral alignment, spectral binning, scaling and normalization. We also provide a set of recommendations for best practices regarding spectral and data processing for NMR-based metabolomic studies of biofluids, with a particular focus on urine.

Recommended strategies for spectral processing and post-processing of 1D 1H-NMR data of biofluids with a particular focus on urine

KAUST Repository

Emwas, Abdul-Hamid M.; Saccenti, Edoardo; Gao, Xin; McKay, Ryan T.; dos Santos, Vitor A. P. Martins; Roy, Raja; Wishart, David S.

2018-01-01

1H NMR spectra from urine can yield information-rich data sets that offer important insights into many biological and biochemical phenomena. However, the quality and utility of these insights can be profoundly affected by how the NMR spectra are processed and interpreted. For instance, if the NMR spectra are incorrectly referenced or inconsistently aligned, the identification of many compounds will be incorrect. If the NMR spectra are mis-phased or if the baseline correction is flawed, the estimated concentrations of many compounds will be systematically biased. Furthermore, because NMR permits the measurement of concentrations spanning up to five orders of magnitude, several problems can arise with data analysis. For instance, signals originating from the most abundant metabolites may prove to be the least biologically relevant while signals arising from the least abundant metabolites may prove to be the most important but hardest to accurately and precisely measure. As a result, a number of data processing techniques such as scaling, transformation and normalization are often required to address these issues. Therefore, proper processing of NMR data is a critical step to correctly extract useful information in any NMR-based metabolomic study. In this review we highlight the significance, advantages and disadvantages of different NMR spectral processing steps that are common to most NMR-based metabolomic studies of urine. These include: chemical shift referencing, phase and baseline correction, spectral alignment, spectral binning, scaling and normalization. We also provide a set of recommendations for best practices regarding spectral and data processing for NMR-based metabolomic studies of biofluids, with a particular focus on urine.

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

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.

Effect of trans fatty acid intake on LC-MS and NMR plasma profiles

DEFF Research Database (Denmark)

Gürdeniz, Gözde; Rago, Daniela; Bendsen, Nathalie Tommerup

2013-01-01

The consumption of high levels of industrial trans fatty acids (TFA) has been related to cardiovascular disease, diabetes and sudden cardiac death but the causal mechanisms are not well known. In this study, NMR and LC-MS untargeted metabolomics has been used as an approach to explore the impact...

NMR/MS Translator for the Enhanced Simultaneous Analysis of Metabolomics Mixtures by NMR Spectroscopy and Mass Spectrometry: Application to Human Urine.

Science.gov (United States)

Bingol, Kerem; Brüschweiler, Rafael

2015-06-05

A novel metabolite identification strategy is presented for the combined NMR/MS analysis of complex metabolite mixtures. The approach first identifies metabolite candidates from 1D or 2D NMR spectra by NMR database query, which is followed by the determination of the masses (m/z) of their possible ions, adducts, fragments, and characteristic isotope distributions. The expected m/z ratios are then compared with the MS(1) spectrum for the direct assignment of those signals of the mass spectrum that contain information about the same metabolites as the NMR spectra. In this way, the mass spectrum can be assigned with very high confidence, and it provides at the same time validation of the NMR-derived metabolites. The method was first demonstrated on a model mixture, and it was then applied to human urine collected from a pool of healthy individuals. A number of metabolites could be detected that had not been reported previously, further extending the list of known urine metabolites. The new analysis approach, which is termed NMR/MS Translator, is fully automated and takes only a few seconds on a computer workstation. NMR/MS Translator synergistically uses the power of NMR and MS, enhancing the accuracy and efficiency of the identification of those metabolites compiled in databases.

Metabolic characterization of Palatinate German white wines according to sensory attributes, varieties, and vintages using NMR spectroscopy and multivariate data analyses

Energy Technology Data Exchange (ETDEWEB)

Ali, Kashif; Maltese, Federica [Leiden University, Division of Pharmacognosy, Section Metabolomics, Institute of Biology (Netherlands); Toepfer, Reinhard [Institute for Grapevine Breeding Geilweilerhof, Julius Kuehn Institute (JKI), Federal Research Centre for Cultivated Plants (Germany); Choi, Young Hae, E-mail: y.choi@chem.leidenuniv.nl; Verpoorte, Robert [Leiden University, Division of Pharmacognosy, Section Metabolomics, Institute of Biology (Netherlands)

2011-04-15

{sup 1}H NMR (nuclear magnetic resonance spectroscopy) has been used for metabolomic analysis of 'Riesling' and 'Mueller-Thurgau' white wines from the German Palatinate region. Diverse two-dimensional NMR techniques have been applied for the identification of metabolites, including phenolics. It is shown that sensory analysis correlates with NMR-based metabolic profiles of wine. {sup 1}H NMR data in combination with multivariate data analysis methods, like principal component analysis (PCA), partial least squares projections to latent structures (PLS), and bidirectional orthogonal projections to latent structures (O2PLS) analysis, were employed in an attempt to identify the metabolites responsible for the taste of wine, using a non-targeted approach. The high quality wines were characterized by elevated levels of compounds like proline, 2,3-butanediol, malate, quercetin, and catechin. Characterization of wine based on type and vintage was also done using orthogonal projections to latent structures (OPLS) analysis. 'Riesling' wines were characterized by higher levels of catechin, caftarate, valine, proline, malate, and citrate whereas compounds like quercetin, resveratrol, gallate, leucine, threonine, succinate, and lactate, were found discriminating for 'Mueller-Thurgau'. The wines from 2006 vintage were dominated by leucine, phenylalanine, citrate, malate, and phenolics, while valine, proline, alanine, and succinate were predominantly present in the 2007 vintage. Based on these results, it can be postulated the NMR-based metabolomics offers an easy and comprehensive analysis of wine and in combination with multivariate data analyses can be used to investigate the source of the wines and to predict certain sensory aspects of wine.

Metabolic characterization of Palatinate German white wines according to sensory attributes, varieties, and vintages using NMR spectroscopy and multivariate data analyses

International Nuclear Information System (INIS)

Ali, Kashif; Maltese, Federica; Toepfer, Reinhard; Choi, Young Hae; Verpoorte, Robert

2011-01-01

1 H NMR (nuclear magnetic resonance spectroscopy) has been used for metabolomic analysis of ‘Riesling’ and ‘Mueller-Thurgau’ white wines from the German Palatinate region. Diverse two-dimensional NMR techniques have been applied for the identification of metabolites, including phenolics. It is shown that sensory analysis correlates with NMR-based metabolic profiles of wine. 1 H NMR data in combination with multivariate data analysis methods, like principal component analysis (PCA), partial least squares projections to latent structures (PLS), and bidirectional orthogonal projections to latent structures (O2PLS) analysis, were employed in an attempt to identify the metabolites responsible for the taste of wine, using a non-targeted approach. The high quality wines were characterized by elevated levels of compounds like proline, 2,3-butanediol, malate, quercetin, and catechin. Characterization of wine based on type and vintage was also done using orthogonal projections to latent structures (OPLS) analysis. ‘Riesling’ wines were characterized by higher levels of catechin, caftarate, valine, proline, malate, and citrate whereas compounds like quercetin, resveratrol, gallate, leucine, threonine, succinate, and lactate, were found discriminating for ‘Mueller-Thurgau’. The wines from 2006 vintage were dominated by leucine, phenylalanine, citrate, malate, and phenolics, while valine, proline, alanine, and succinate were predominantly present in the 2007 vintage. Based on these results, it can be postulated the NMR-based metabolomics offers an easy and comprehensive analysis of wine and in combination with multivariate data analyses can be used to investigate the source of the wines and to predict certain sensory aspects of wine.

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

Science.gov (United States)

Ghaste, Manoj; Mistrik, Robert; Shulaev, Vladimir

2016-01-01

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

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.

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.

Metabolomics reveals energetic impairments in Daphnia magna exposed to diazinon, malathion and bisphenol-A

Energy Technology Data Exchange (ETDEWEB)

Nagato, Edward G.; Simpson, André J.; Simpson, Myrna J., E-mail: myrna.simpson@utoronto.ca

2016-01-15

Highlights: • Metabolomics detected shifts with sub-lethal exposure to contaminants. • Diazinon and malathion induced comparable, non-linear responses. • Bisphenol-A resulted in energy impairment. • Overall, insight into sub-lethal toxicity was garnered using NMR-based metabolomics. - Abstract: {sup 1}H nuclear magnetic resonance (NMR)-based metabolomics was used to study the response of Daphnia magna to increasing sub-lethal concentrations of either an organophosphate (diazinon or malathion) or bisphenol-A (BPA). Principal component analysis (PCA) of {sup 1}H NMR spectra were used to screen metabolome changes after 48 h of contaminant exposure. The PCA scores plots showed that diazinon exposures resulted in aberrant metabolomic profiles at all exposure concentrations tested (0.009–0.135 μg/L), while for malathion the second lowest (0.08 μg/L) and two highest exposure concentrations (0.32 μg/L and 0.47 μg/L) caused significant shifts from the control. Individual metabolite changes for both organophosphates indicated that the response to increasing exposure was non-linear and described perturbations in the metabolome that were characteristic of the severity of exposure. For example, intermediate concentrations of diazinon (0.045 μg/L and 0.09 μg/L) and malathion (0.08 μg/L) elicited a decrease in amino acids such as leucine, valine, arginine, glycine, lysine, glutamate, glutamine, phenylalanine and tyrosine, with concurrent increases in glucose and lactate, suggesting a mobilization of energy resources to combat stress. At the highest exposure concentrations for both organophosphates there was evidence of a cessation in metabolic activity, where the same amino acids increased and glucose and lactate decreased, suggesting a slowdown in protein synthesis and depletion of energy stocks. This demonstrated a similar response in the metabolome between two organophosphates but also that intermediate and severe stress levels could be differentiated by

{sup 1}H NMR-based metabolic profiling reveals inherent biological variation in yeast and nematode model systems

Energy Technology Data Exchange (ETDEWEB)

Szeto, Samuel S. W.; Reinke, Stacey N.; Lemire, Bernard D., E-mail: bernard.lemire@ualberta.ca [University of Alberta, Department of Biochemistry, School of Molecular and Systems Medicine (Canada)

2011-04-15

The application of metabolomics to human and animal model systems is poised to provide great insight into our understanding of disease etiology and the metabolic changes that are associated with these conditions. However, metabolomic studies have also revealed that there is significant, inherent biological variation in human samples and even in samples from animal model systems where the animals are housed under carefully controlled conditions. This inherent biological variability is an important consideration for all metabolomics analyses. In this study, we examined the biological variation in {sup 1}H NMR-based metabolic profiling of two model systems, the yeast Saccharomyces cerevisiae and the nematode Caenorhabditis elegans. Using relative standard deviations (RSD) as a measure of variability, our results reveal that both model systems have significant amounts of biological variation. The C. elegans metabolome possesses greater metabolic variance with average RSD values of 29 and 39%, depending on the food source that was used. The S. cerevisiae exometabolome RSD values ranged from 8% to 12% for the four strains examined. We also determined whether biological variation occurs between pairs of phenotypically identical yeast strains. Multivariate statistical analysis allowed us to discriminate between pair members based on their metabolic phenotypes. Our results highlight the variability of the metabolome that exists even for less complex model systems cultured under defined conditions. We also highlight the efficacy of metabolic profiling for defining these subtle metabolic alterations.

Integration of datasets from different analytical techniques to assess the impact of nutrition on human metabolome

Directory of Open Access Journals (Sweden)

Pamela eVernocchi

2012-12-01

Full Text Available Bacteria colonizing the human intestinal tract exhibit a high phylogenetic diversity that reflects their immense metabolic potentials. The catalytic activity of gut microbes has an important impact on gastrointestinal (GI functions and host health. The microbial conversion of carbohydrates and other food components leads to the formation of a large number of compounds that affect the host metabolome and have beneficial or adverse effects on human health. Meabolomics is a metabolic-biology system approach focused on the metabolic responses understanding of living systems to physio-pathological stimuli by using multivariate statistical data on human body fluids obtained by different instrumental techniques. A metabolomic approach based on an analytical platform could be able to separate, detect, characterize and quantify a wide range of metabolites and its metabolic pathways. This approach has been recently applied to study the metabolic changes triggered in the gut microbiota by specific diet components and diet variations, specific diseases, probiotic and synbiotic food intake.This review describes the metabolomic data obtained by analyzing human fluids by using different techniques and particularly Gas Chromatography Mass Spectrometry Solid-phase Micro Extraction (GC-MS/SPME, Proton Nuclear Magnetic Resonance (1H-NMR Spectroscopy and Fourier Transform Infrared (FTIR Spectroscopy. This instrumental approach have a good potential in the identification and detection of specific food intake and diseases biomarkers.

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

NMR-Fragment Based Virtual Screening: A Brief Overview.

Science.gov (United States)

Singh, Meenakshi; Tam, Benjamin; Akabayov, Barak

2018-01-25

Fragment-based drug discovery (FBDD) using NMR has become a central approach over the last twenty years for development of small molecule inhibitors against biological macromolecules, to control a variety of cellular processes. Yet, several considerations should be taken into account for obtaining a therapeutically relevant agent. In this review, we aim to list the considerations that make NMR fragment screening a successful process for yielding potent inhibitors. Factors that may govern the competence of NMR in fragment based drug discovery are discussed, as well as later steps that involve optimization of hits obtained by NMR-FBDD.

NMR-Fragment Based Virtual Screening: A Brief Overview

Directory of Open Access Journals (Sweden)

Meenakshi Singh

2018-01-01

Full Text Available Fragment-based drug discovery (FBDD using NMR has become a central approach over the last twenty years for development of small molecule inhibitors against biological macromolecules, to control a variety of cellular processes. Yet, several considerations should be taken into account for obtaining a therapeutically relevant agent. In this review, we aim to list the considerations that make NMR fragment screening a successful process for yielding potent inhibitors. Factors that may govern the competence of NMR in fragment based drug discovery are discussed, as well as later steps that involve optimization of hits obtained by NMR-FBDD.

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

Science.gov (United States)

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

2018-09-26

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

The Human Urine Metabolome

Science.gov (United States)

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

2013-01-01

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

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 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 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...

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

Science.gov (United States)

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

Metabolome Profiling by HRMAS NMR Spectroscopy of Pheochromocytomas and Paragangliomas Detects SDH Deficiency: Clinical and Pathophysiological Implications

Directory of Open Access Journals (Sweden)

Alessio Imperiale

2015-01-01

Full Text Available Succinate dehydrogenase gene (SDHx mutations increase susceptibility to develop pheochromocytomas/paragangliomas (PHEOs/PGLs. In the present study, we evaluate the performance and clinical applications of 1H high-resolution magic angle spinning (HRMAS nuclear magnetic resonance (NMR spectroscopy–based global metabolomic profiling in a large series of PHEOs/PGLs of different genetic backgrounds. Eighty-seven PHEOs/PGLs (48 sporadic/23 SDHx/7 von Hippel-Lindau/5 REarranged during Transfection/3 neurofibromatosis type 1/1 hypoxia-inducible factor 2α, one SDHD variant of unknown significance, and two Carney triad (CTr–related tumors were analyzed by HRMAS-NMR spectroscopy. Compared to sporadic, SDHx-related PHEOs/PGLs exhibit a specific metabolic signature characterized by increased levels of succinate (P < .0001, methionine (P = .002, glutamine (P = .002, and myoinositol (P < .0007 and decreased levels of glutamate (P < .0007, regardless of their location and catecholamine levels. Uniquely, ATP/ascorbate/glutathione was found to be associated with the secretory phenotype of PHEOs/PGLs, regardless of their genotype (P < .0007. The use of succinate as a single screening test retained excellent accuracy in distinguishing SDHx versus non–SDHx-related tumors (sensitivity/specificity: 100/100%. Moreover, the quantification of succinate could be considered a diagnostic alternative for assessing SDHx-related mutations of unknown pathogenicity. We were also able, for the first time, to uncover an SDH-like pattern in the two CTr-related PGLs. The present study demonstrates that HRMAS-NMR provides important information for SDHx-related PHEO/PGL characterization. Besides the high succinate–low glutamate hallmark, SDHx tumors also exhibit high values of methionine, a finding consistent with the hypermethylation pattern of these tumors. We also found important levels of glutamine, suggesting that glutamine metabolism might be involved in the

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

Science.gov (United States)

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

2017-10-01

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

NMR-based approach to the analysis of radiopharmaceuticals: radiochemical purity, specific activity, and radioactive concentration values by proton and tritium NMR spectroscopy.

Science.gov (United States)

Schenk, David J; Dormer, Peter G; Hesk, David; Pollack, Scott R; Lavey, Carolee Flader

2015-06-15

Compounds containing tritium are widely used across the drug discovery and development landscape. These materials are widely utilized because they can be efficiently synthesized and produced at high specific activity. Results from internally calibrated (3)H and (1)H nuclear magnetic resonance (NMR) spectroscopy suggests that at least in some cases, this calibrated approach could supplement or potentially replace radio-high-performance liquid chromatography for radiochemical purity, dilution and scintillation counting for the measurement of radioactivity per volume, and liquid chromatography/mass spectrometry analysis for the determination of specific activity. In summary, the NMR-derived values agreed with those from the standard approaches to within 1% to 9% for solution count and specific activity. Additionally, the NMR-derived values for radiochemical purity deviated by less than 5%. A benefit of this method is that these values may be calculated at the same time that (3)H NMR analysis provides the location and distribution of tritium atoms within the molecule. Presented and discussed here is the application of this method, advantages and disadvantages of the approach, and a rationale for utilizing internally calibrated (1)H and (3)H NMR spectroscopy for specific activity, radioactive concentration, and radiochemical purity whenever acquiring (3)H NMR for tritium location. Copyright © 2015 John Wiley & Sons, Ltd.

Characterization and Discrimination of Ancient Grains: A Metabolomics Approach

Directory of Open Access Journals (Sweden)

Laura Righetti

2016-07-01

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

Classification of Ilex species based on metabolomic fingerprinting using nuclear magnetic resonance and multivariate data analysis.

Science.gov (United States)

Choi, Young Hae; Sertic, Sarah; Kim, Hye Kyong; Wilson, Erica G; Michopoulos, Filippos; Lefeber, Alfons W M; Erkelens, Cornelis; Prat Kricun, Sergio D; Verpoorte, Robert

2005-02-23

The metabolomic analysis of 11 Ilex species, I. argentina, I. brasiliensis, I. brevicuspis, I. dumosavar. dumosa, I. dumosa var. guaranina, I. integerrima, I. microdonta, I. paraguariensis var. paraguariensis, I. pseudobuxus, I. taubertiana, and I. theezans, was carried out by NMR spectroscopy and multivariate data analysis. The analysis using principal component analysis and classification of the (1)H NMR spectra showed a clear discrimination of those samples based on the metabolites present in the organic and aqueous fractions. The major metabolites that contribute to the discrimination are arbutin, caffeine, phenylpropanoids, and theobromine. Among those metabolites, arbutin, which has not been reported yet as a constituent of Ilex species, was found to be a biomarker for I. argentina,I. brasiliensis, I. brevicuspis, I. integerrima, I. microdonta, I. pseudobuxus, I. taubertiana, and I. theezans. This reliable method based on the determination of a large number of metabolites makes the chemotaxonomical analysis of Ilex species possible.

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.

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)

Metabolomic profiling of rapid cold hardening and cold shock in Drosophila melanogaster

DEFF Research Database (Denmark)

Overgaard, Johannes; Malmendal, Anders; Sørensen, Jesper

2007-01-01

study used untargeted (1)H NMR metabolomic profiling to examine the metabolomic response in Drosophila melanogaster during the 72 h following RCH and cold shock treatment. These findings are discussed in relation to the costs and benefits of RCH that are measured in terms of survival and reproductive...

Metabolic Profiling and Classification of Propolis Samples from Southern Brazil: An NMR-Based Platform Coupled with Machine Learning.

Science.gov (United States)

Maraschin, Marcelo; Somensi-Zeggio, Amélia; Oliveira, Simone K; Kuhnen, Shirley; Tomazzoli, Maíra M; Raguzzoni, Josiane C; Zeri, Ana C M; Carreira, Rafael; Correia, Sara; Costa, Christopher; Rocha, Miguel

2016-01-22

The chemical composition of propolis is affected by environmental factors and harvest season, making it difficult to standardize its extracts for medicinal usage. By detecting a typical chemical profile associated with propolis from a specific production region or season, certain types of propolis may be used to obtain a specific pharmacological activity. In this study, propolis from three agroecological regions (plain, plateau, and highlands) from southern Brazil, collected over the four seasons of 2010, were investigated through a novel NMR-based metabolomics data analysis workflow. Chemometrics and machine learning algorithms (PLS-DA and RF), including methods to estimate variable importance in classification, were used in this study. The machine learning and feature selection methods permitted construction of models for propolis sample classification with high accuracy (>75%, reaching ∼90% in the best case), better discriminating samples regarding their collection seasons comparatively to the harvest regions. PLS-DA and RF allowed the identification of biomarkers for sample discrimination, expanding the set of discriminating features and adding relevant information for the identification of the class-determining metabolites. The NMR-based metabolomics analytical platform, coupled to bioinformatic tools, allowed characterization and classification of Brazilian propolis samples regarding the metabolite signature of important compounds, i.e., chemical fingerprint, harvest seasons, and production regions.

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.

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.

Systematic Applications of Metabolomics in Metabolic Engineering

Directory of Open Access Journals (Sweden)

Robert A. Dromms

2012-12-01

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

Haystack, a web-based tool for metabolomics research.

Science.gov (United States)

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

2014-01-01

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

Suitability of dried herbarium specimens for NMR metabolomics of mushrooms. A comparison of four species of the genera Kuehneromyces and Hypholoma (Strophariaceae).

Science.gov (United States)

Jafari, Tahereh; Alanne, Aino-Liisa; Issakainen, Jouni; Pihlaja, Kati; Sinkkonen, Jari

Herbarium specimens are a treasure trove for biochemical studies. However, this implies understanding of the chemical changes during the drying and storage of the specimen. We compared herbarium specimens at different ages and fresh samples of four mushroom species (Kuehneromyces mutabilis, Hypholoma capnoides, Kuehneromyces lignicola, Hypholoma fasciculare) of two genera in the family Strophariaceae by using proton nuclear magnetic resonance ( 1 H NMR) spectroscopy combined with principal component analysis (PCA). 25 metabolites were identified. No significant alterations were found between herbarium samples at different ages, suggesting that they are stable enough for comparative studies. The most dominant differences between fresh and herbarium samples was that sugars such as α-α-trehalose, and fumaric and malic acids were more abundant in fresh fungi. Total contents of fatty and amino acids, uracil and γ-aminobutyric acid (GABA) were higher in herbarium specimens. In addition, pyroglutamic acid was observed only in Kuehneromyces mutabilis and fasciculic acid E in Hypholomafasciculare. Hence, based on results of the studied taxa, we conclude that NMR metabolomics can be used for both fresh and dried mushrooms when such alterations are properly addressed. Copyright © 2017 British Mycological Society. Published by Elsevier Ltd. All rights reserved.

Metabolomic applications to decipher gut microbial metabolic influence in health and disease

Directory of Open Access Journals (Sweden)

Francois-Pierre eMartin

2012-04-01

Full Text Available Dietary preferences and nutrients composition have been shown to influence human and gut microbial metabolism, which ultimately has specific effects on health and diseases’ risk. Increasingly, results from molecular biology and microbiology demonstrate the key role of the gut microbiota metabolic interface to the overall mammalian host’s health status. There is therefore raising interest in nutrition research to characterize the molecular foundations of the gut microbial mammalian cross-talk at both physiological and biochemical pathway levels. Tackling these challenges can be achieved through systems biology approaches, such as metabolomics, to underpin the highly complex metabolic exchanges between diverse biological compartments, including organs, systemic biofluids and microbial symbionts. By the development of specific biomarkers for prediction of health and disease, metabolomics is increasingly used in clinical applications as regard to disease aetiology, diagnostic stratification and potentially mechanism of action of therapeutical and nutraceutical solutions. Surprisingly, an increasing number of metabolomics investigations in pre-clinical and clinical studies based on proton nuclear magnetic resonance (1H NMR spectroscopy and mass spectrometry (MS provided compelling evidence that system wide and organ-specific biochemical processes are under the influence of gut microbial metabolism. This review aims at describing recent applications of metabolomics in clinical fields where main objective is to discern the biochemical mechanisms under the influence of the gut microbiota, with insight into gastrointestinal health and diseases diagnostics and improvement of homeostasis metabolic regulation.

Untargeted Metabolomics Strategies—Challenges and Emerging Directions

Science.gov (United States)

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

2016-12-01

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

Metabolomics of Oxidative Stress in Recent Studies of Endogenous and Exogenously Administered Intermediate Metabolites

Directory of Open Access Journals (Sweden)

Jeffrey G. Pelton

2011-09-01

Full Text Available Aerobic metabolism occurs in a background of oxygen radicals and reactive oxygen species (ROS that originate from the incomplete reduction of molecular oxygen in electron transfer reactions. The essential role of aerobic metabolism, the generation and consumption of ATP and other high energy phosphates, sustains a balance of approximately 3000 essential human metabolites that serve not only as nutrients, but also as antioxidants, neurotransmitters, osmolytes, and participants in ligand-based and other cellular signaling. In hypoxia, ischemia, and oxidative stress, where pathological circumstances cause oxygen radicals to form at a rate greater than is possible for their consumption, changes in the composition of metabolite ensembles, or metabolomes, can be associated with physiological changes. Metabolomics and metabonomics are a scientific disciplines that focuse on quantifying dynamic metabolome responses, using multivariate analytical approaches derived from methods within genomics, a discipline that consolidated innovative analysis techniques for situations where the number of biomarkers (metabolites in our case greatly exceeds the number of subjects. This review focuses on the behavior of cytosolic, mitochondrial, and redox metabolites in ameliorating or exacerbating oxidative stress. After reviewing work regarding a small number of metabolites—pyruvate, ethyl pyruvate, and fructose-1,6-bisphosphate—whose exogenous administration was found to ameliorate oxidative stress, a subsequent section reviews basic multivariate statistical methods common in metabolomics research, and their application in human and preclinical studies emphasizing oxidative stress. Particular attention is paid to new NMR spectroscopy methods in metabolomics and metabonomics. Because complex relationships connect oxidative stress to so many physiological processes, studies from different disciplines were reviewed. All, however, shared the common goal of ultimately

Metabolomics of Oxidative Stress in Recent Studies of Endogenous and Exogenously Administered Intermediate Metabolites

Science.gov (United States)

Liu, Jia; Litt, Lawrence; Segal, Mark R.; Kelly, Mark J. S.; Pelton, Jeffrey G.; Kim, Myungwon

2011-01-01

Aerobic metabolism occurs in a background of oxygen radicals and reactive oxygen species (ROS) that originate from the incomplete reduction of molecular oxygen in electron transfer reactions. The essential role of aerobic metabolism, the generation and consumption of ATP and other high energy phosphates, sustains a balance of approximately 3000 essential human metabolites that serve not only as nutrients, but also as antioxidants, neurotransmitters, osmolytes, and participants in ligand-based and other cellular signaling. In hypoxia, ischemia, and oxidative stress, where pathological circumstances cause oxygen radicals to form at a rate greater than is possible for their consumption, changes in the composition of metabolite ensembles, or metabolomes, can be associated with physiological changes. Metabolomics and metabonomics are a scientific disciplines that focuse on quantifying dynamic metabolome responses, using multivariate analytical approaches derived from methods within genomics, a discipline that consolidated innovative analysis techniques for situations where the number of biomarkers (metabolites in our case) greatly exceeds the number of subjects. This review focuses on the behavior of cytosolic, mitochondrial, and redox metabolites in ameliorating or exacerbating oxidative stress. After reviewing work regarding a small number of metabolites—pyruvate, ethyl pyruvate, and fructose-1,6-bisphosphate—whose exogenous administration was found to ameliorate oxidative stress, a subsequent section reviews basic multivariate statistical methods common in metabolomics research, and their application in human and preclinical studies emphasizing oxidative stress. Particular attention is paid to new NMR spectroscopy methods in metabolomics and metabonomics. Because complex relationships connect oxidative stress to so many physiological processes, studies from different disciplines were reviewed. All, however, shared the common goal of ultimately developing “omics”-based

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

[Using (1)H-nuclear magnetic resonance metabolomics and gene ontology to establish pathological staging model for esophageal cancer patients].

Science.gov (United States)

Chen, X; Wang, K; Chen, W; Jiang, H; Deng, P C; Li, Z J; Peng, J; Zhou, Z Y; Yang, H; Huang, G X; Zeng, J

2016-07-01

(ethanol amine, hydroxy-propionic acid, homocysteine and estriol) were eventually selected. gene ontology analysis showed that 54 enzymes and genes regulated the 4 key metabolic markers. The quantitative prediction model of esophageal cancer staging based on esophageal cancer NMR spectrum were established. Cross-validation results showed that the predicted effect was good (root mean square error=5.3, R(2)=0.47, P=0.036). The systems biology approaches based on metabolomics and enzyme-gene regulatory network analysis can be used to quantify the metabolic network disturbance of patients with advanced esophageal cancer, and to predict preoperative clinical staging of esophageal cancer patients by plasma NMR metabolomics.

NMR (1H and 13C) based signatures of abnormal choline metabolism in oral squamous cell carcinoma with no prominent Warburg effect

International Nuclear Information System (INIS)

Bag, Swarnendu; Banerjee, Deb Ranjan; Basak, Amit; Das, Amit Kumar; Pal, Mousumi; Banerjee, Rita; Paul, Ranjan Rashmi; Chatterjee, Jyotirmoy

2015-01-01

At functional levels, besides genes and proteins, changes in metabolome profiles are instructive for a biological system in health and disease including malignancy. It is understood that metabolomic alterations in association with proteomic and transcriptomic aberrations are very fundamental to unravel malignant micro-ambient criticality and oral cancer is no exception. Hence deciphering intricate dimensions of oral cancer metabolism may be contributory both for integrated appreciation of its pathogenesis and to identify any critical but yet unexplored dimension of this malignancy with high mortality rate. Although several methods do exist, NMR provides higher analytical precision in identification of cancer metabolomic signature. Present study explored abnormal signatures in choline metabolism in oral squamous cell carcinoma (OSCC) using 1 H and 13 C NMR analysis of serum. It has demonstrated down-regulation of choline with concomitant up-regulation of its break-down product in the form of trimethylamine N-oxide in OSCC compared to normal counterpart. Further, no significant change in lactate profile in OSCC possibly indicated that well-known Warburg effect was not a prominent phenomenon in such malignancy. Amongst other important metabolites, malonate has shown up-regulation but D-glucose, saturated fatty acids, acetate and threonine did not show any significant change. Analyzing these metabolomic findings present study proposed trimethyl amine N-oxide and malonate as important metabolic signature for oral cancer with no prominent Warburg effect. - Highlights: • NMR ( 1 H and 13 C) study of Oral Squamous cell Carcinoma Serum. • Abnormal Choline metabolomic signatures. • Up-regulation of Trimethylamine N-oxide. • Unchanged lactate profile indicates no prominent Warburg effect. • Proposed alternative glucose metabolism path through up-regulation of malonate

Urinary 1H Nuclear Magnetic Resonance Metabolomic Fingerprinting Reveals Biomarkers of Pulse Consumption Related to Energy-Metabolism Modulation in a Subcohort from the PREDIMED study.

Science.gov (United States)

Madrid-Gambin, Francisco; Llorach, Rafael; Vázquez-Fresno, Rosa; Urpi-Sarda, Mireia; Almanza-Aguilera, Enrique; Garcia-Aloy, Mar; Estruch, Ramon; Corella, Dolores; Andres-Lacueva, Cristina

2017-04-07

Little is known about the metabolome fingerprint of pulse consumption. The study of robust and accurate biomarkers for pulse dietary assessment has great value for nutritional epidemiology regarding health benefits and their mechanisms. To characterize the fingerprinting of dietary pulses (chickpeas, lentils, and beans), spot urine samples from a subcohort from the PREDIMED study were stratified using a validated food frequency questionnaire. Urine samples of nonpulse consumers (≤4 g/day of pulse intake) and habitual pulse consumers (≥25 g/day of pulse intake) were analyzed using a 1 H nuclear magnetic resonance (NMR) metabolomics approach combined with multi- and univariate data analysis. Pulse consumption showed differences through 16 metabolites coming from (i) choline metabolism, (ii) protein-related compounds, and (iii) energy metabolism (including lower urinary glucose). Stepwise logistic regression analysis was applied to design a combined model of pulse exposure, which resulted in glutamine, dimethylamine, and 3-methylhistidine. This model was evaluated by a receiver operating characteristic curve (AUC > 90% in both training and validation sets). The application of NMR-based metabolomics to reported pulse exposure highlighted new candidates for biomarkers of pulse consumption and the impact on energy metabolism, generating new hypotheses on energy modulation. Further intervention studies will confirm these findings.

NMR-based metabolomics of water-buffalo milk after conventional or biological feeding

Directory of Open Access Journals (Sweden)

Pierluigi Mazzei

2018-02-01

Full Text Available Abstract Background Biological farming in dairy production is often advocated as one of the most virtuous solutions to the environmental problems of conventional farming while improving the sustainability of production and cattle welfare. However, it is still under debate whether the conversion from conventional to biological farming has an influence on milk composition. In addition, the possible frauds related to biological dairy products call for analytical tools enabling the authentication of products quality and consumers protection. The aim of this work was to determine the composition of milk produced by water-buffaloes and to identify the specific metabolic profiles discriminating a biological from a conventional feeding diet. Methods Liquid-state 1H, 13C, and 31P nuclear magnetic resonance (NMR spectroscopies were used to study milk samples which were supplied during a 2-year-long experimentation by a single dairy farm and sampled from conventionally and biologically fed buffaloes (CFM and BFM, respectively. For each milk sample, we obtained NMR spectra of both raw milk and milk cream fractions comprising neutral lipids and phospholipids. Results The elaboration of multinuclear spectroscopic NMR results by the principal component analysis (PCA enabled the identification of diagnostic differences in the milk composition between CFM and BFM samples. In particular, BFM were characterized by larger content of unsaturated lipids and phosphatidylcholine. Our findings confirmed that the conversion from a conventional to biological feeding regime influenced the buffalo milk composition, with possible implications for sensorial and nutritional properties of dairy products. Finally, the analytical methodology of NMR spectroscopy shown here may be considered as a useful tool to assess the quality and the authenticity of biological milk.

Bayesian deconvolution and quantification of metabolites in complex 1D NMR spectra using BATMAN.

Science.gov (United States)

Hao, Jie; Liebeke, Manuel; Astle, William; De Iorio, Maria; Bundy, Jacob G; Ebbels, Timothy M D

2014-01-01

Data processing for 1D NMR spectra is a key bottleneck for metabolomic and other complex-mixture studies, particularly where quantitative data on individual metabolites are required. We present a protocol for automated metabolite deconvolution and quantification from complex NMR spectra by using the Bayesian automated metabolite analyzer for NMR (BATMAN) R package. BATMAN models resonances on the basis of a user-controllable set of templates, each of which specifies the chemical shifts, J-couplings and relative peak intensities for a single metabolite. Peaks are allowed to shift position slightly between spectra, and peak widths are allowed to vary by user-specified amounts. NMR signals not captured by the templates are modeled non-parametrically by using wavelets. The protocol covers setting up user template libraries, optimizing algorithmic input parameters, improving prior information on peak positions, quality control and evaluation of outputs. The outputs include relative concentration estimates for named metabolites together with associated Bayesian uncertainty estimates, as well as the fit of the remainder of the spectrum using wavelets. Graphical diagnostics allow the user to examine the quality of the fit for multiple spectra simultaneously. This approach offers a workflow to analyze large numbers of spectra and is expected to be useful in a wide range of metabolomics studies.

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

Science.gov (United States)

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

2011-05-20

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

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

Science.gov (United States)

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

2016-01-01

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

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.

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.

Principal component directed partial least squares analysis for combining nuclear magnetic resonance and mass spectrometry data in metabolomics: Application to the detection of breast cancer

International Nuclear Information System (INIS)

Gu Haiwei; Pan Zhengzheng; Xi Bowei; Asiago, Vincent; Musselman, Brian; Raftery, Daniel

2011-01-01

Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) are the two most commonly used analytical tools in metabolomics, and their complementary nature makes the combination particularly attractive. A combined analytical approach can improve the potential for providing reliable methods to detect metabolic profile alterations in biofluids or tissues caused by disease, toxicity, etc. In this paper, 1 H NMR spectroscopy and direct analysis in real time (DART)-MS were used for the metabolomics analysis of serum samples from breast cancer patients and healthy controls. Principal component analysis (PCA) of the NMR data showed that the first principal component (PC1) scores could be used to separate cancer from normal samples. However, no such obvious clustering could be observed in the PCA score plot of DART-MS data, even though DART-MS can provide a rich and informative metabolic profile. Using a modified multivariate statistical approach, the DART-MS data were then reevaluated by orthogonal signal correction (OSC) pretreated partial least squares (PLS), in which the Y matrix in the regression was set to the PC1 score values from the NMR data analysis. This approach, and a similar one using the first latent variable from PLS-DA of the NMR data resulted in a significant improvement of the separation between the disease samples and normals, and a metabolic profile related to breast cancer could be extracted from DART-MS. The new approach allows the disease classification to be expressed on a continuum as opposed to a binary scale and thus better represents the disease and healthy classifications. An improved metabolic profile obtained by combining MS and NMR by this approach may be useful to achieve more accurate disease detection and gain more insight regarding disease mechanisms and biology.

Principal component directed partial least squares analysis for combining nuclear magnetic resonance and mass spectrometry data in metabolomics: application to the detection of breast cancer.

Science.gov (United States)

Gu, Haiwei; Pan, Zhengzheng; Xi, Bowei; Asiago, Vincent; Musselman, Brian; Raftery, Daniel

2011-02-07

Nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) are the two most commonly used analytical tools in metabolomics, and their complementary nature makes the combination particularly attractive. A combined analytical approach can improve the potential for providing reliable methods to detect metabolic profile alterations in biofluids or tissues caused by disease, toxicity, etc. In this paper, (1)H NMR spectroscopy and direct analysis in real time (DART)-MS were used for the metabolomics analysis of serum samples from breast cancer patients and healthy controls. Principal component analysis (PCA) of the NMR data showed that the first principal component (PC1) scores could be used to separate cancer from normal samples. However, no such obvious clustering could be observed in the PCA score plot of DART-MS data, even though DART-MS can provide a rich and informative metabolic profile. Using a modified multivariate statistical approach, the DART-MS data were then reevaluated by orthogonal signal correction (OSC) pretreated partial least squares (PLS), in which the Y matrix in the regression was set to the PC1 score values from the NMR data analysis. This approach, and a similar one using the first latent variable from PLS-DA of the NMR data resulted in a significant improvement of the separation between the disease samples and normals, and a metabolic profile related to breast cancer could be extracted from DART-MS. The new approach allows the disease classification to be expressed on a continuum as opposed to a binary scale and thus better represents the disease and healthy classifications. An improved metabolic profile obtained by combining MS and NMR by this approach may be useful to achieve more accurate disease detection and gain more insight regarding disease mechanisms and biology. Copyright © 2010 Elsevier B.V. All rights reserved.

On the Traceability of Commercial Saffron Samples Using 1H-NMR and FT-IR Metabolomics

Directory of Open Access Journals (Sweden)

Roberto Consonni

2016-02-01

Full Text Available In previous works on authentic samples of saffron of known history (harvest and processing year, storage conditions, and length of time some biomarkers were proposed using both FT-IR and NMR metabolomics regarding the shelf life of the product. This work addresses the difficulties to trace back the “age” of commercial saffron samples of unknown history, sets a limit value above which these products can be considered substandard, and offers a useful tool to combat saffron mislabeling and fraud with low-quality saffron material. Investigations of authentic and commercial saffron samples of different origin and harvest year, which had been stored under controlled conditions for different lengths of time, allowed a clear-cut clustering of samples in two groups according to the storage period irrespectively of the provenience. In this respect, the four-year cut off point proposed in our previous work assisted to trace back the “age” of unknown samples and to check for possible mislabeling practices.

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.

Integration of metabolomics data into metabolic networks.

Science.gov (United States)

Töpfer, Nadine; Kleessen, Sabrina; Nikoloski, Zoran

2015-01-01

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

Metabolomics as a promising tool for early osteoarthritis diagnosis

Directory of Open Access Journals (Sweden)

E.B. de Sousa

2017-09-01

Full Text Available Osteoarthritis (OA is the main cause of disability worldwide, due to progressive articular cartilage loss and degeneration. According to recent research, OA is more than just a degenerative disease due to some metabolic components associated to its pathogenesis. However, no biomarker has been identified to detect this disease at early stages or to track its development. Metabolomics is an emerging field and has the potential to detect many metabolites in a single spectrum using high resolution nuclear magnetic resonance (NMR techniques or mass spectrometry (MS. NMR is a reproducible and reliable non-destructive analytical method. On the other hand, MS has a lower detection limit and is more destructive, but it is more sensitive. NMR and MS are useful for biological fluids, such as urine, blood plasma, serum, or synovial fluid, and have been used for metabolic profiling in dogs, mice, sheep, and humans. Thus, many metabolites have been listed as possibly associated to OA pathogenesis. The goal of this review is to provide an overview of the studies in animal models and humans, regarding the use of metabolomics as a tool for early osteoarthritis diagnosis. The concept of osteoarthritis as a metabolic disease and the importance of detecting a biomarker for its early diagnosis are highlighted. Then, some studies in plasma and synovial tissues are shown, and finally the application of metabolomics in the evaluation of synovial fluid is described.

NMR ({sup 1}H and {sup 13}C) based signatures of abnormal choline metabolism in oral squamous cell carcinoma with no prominent Warburg effect

Energy Technology Data Exchange (ETDEWEB)

Bag, Swarnendu, E-mail: Swarna.bag@gmail.com [School of Medical Science and Technology, Indian Institute of Technology-Kharagpur, 721302 West Bengal (India); Banerjee, Deb Ranjan, E-mail: debranjan2@gmail.com [Department of Chemistry, Indian Institute of Technology-Kharagpur, 721302 West Bengal (India); Basak, Amit, E-mail: absk@chem.iitkgp.ernet.in [Department of Chemistry, Indian Institute of Technology-Kharagpur, 721302 West Bengal (India); Das, Amit Kumar, E-mail: amitk@hijli.iitkgp.ernet.in [Department of Biotechnology, Indian Institute of Technology-Kharagpur, 721302 West Bengal (India); Pal, Mousumi, E-mail: drmpal62@gmail.com [Department of Oral and Maxillofacial Pathology, Guru Nanak Institute of Dental Sciences and Research, Kolkata, West Bengal (India); Banerjee, Rita, E-mail: ritabanerjee@outlook.com [Department of Science and Technology, New Mehrauli Road, New Delhi 110016 (India); Paul, Ranjan Rashmi, E-mail: dr_rsspaul@yahoo.co.in [Department of Oral and Maxillofacial Pathology, Guru Nanak Institute of Dental Sciences and Research, Kolkata, West Bengal (India); Chatterjee, Jyotirmoy, E-mail: jchatterjee.iitkgp@gmail.com [School of Medical Science and Technology, Indian Institute of Technology-Kharagpur, 721302 West Bengal (India)

2015-04-17

At functional levels, besides genes and proteins, changes in metabolome profiles are instructive for a biological system in health and disease including malignancy. It is understood that metabolomic alterations in association with proteomic and transcriptomic aberrations are very fundamental to unravel malignant micro-ambient criticality and oral cancer is no exception. Hence deciphering intricate dimensions of oral cancer metabolism may be contributory both for integrated appreciation of its pathogenesis and to identify any critical but yet unexplored dimension of this malignancy with high mortality rate. Although several methods do exist, NMR provides higher analytical precision in identification of cancer metabolomic signature. Present study explored abnormal signatures in choline metabolism in oral squamous cell carcinoma (OSCC) using {sup 1}H and {sup 13}C NMR analysis of serum. It has demonstrated down-regulation of choline with concomitant up-regulation of its break-down product in the form of trimethylamine N-oxide in OSCC compared to normal counterpart. Further, no significant change in lactate profile in OSCC possibly indicated that well-known Warburg effect was not a prominent phenomenon in such malignancy. Amongst other important metabolites, malonate has shown up-regulation but D-glucose, saturated fatty acids, acetate and threonine did not show any significant change. Analyzing these metabolomic findings present study proposed trimethyl amine N-oxide and malonate as important metabolic signature for oral cancer with no prominent Warburg effect. - Highlights: • NMR ({sup 1}H and {sup 13}C) study of Oral Squamous cell Carcinoma Serum. • Abnormal Choline metabolomic signatures. • Up-regulation of Trimethylamine N-oxide. • Unchanged lactate profile indicates no prominent Warburg effect. • Proposed alternative glucose metabolism path through up-regulation of malonate.

1H High Resolution Magic-Angle Coil Spinning (HR-MACS µNMR Metabolic Profiling of whole Saccharomyces cervisiae cells: A Demonstrative Study

Directory of Open Access Journals (Sweden)

Alan eWong

2014-06-01

Full Text Available The low sensitivity of Nuclear Magnetic Resonance (NMR is its prime shortcoming compared to other analytical methods for metabolomic studies. It relies on large sample volume (30–50 µl for HR-MAS for rich metabolic profiling, hindering high-throughput screening especially when the sample requires a labor-intensive preparation or is a sacred specimen. This is indeed the case for some living organisms. This study evaluates a 1H HR-MAS approach for metabolic profiling of small volume (250 nl whole bacterial cells, Saccharomyces cervisiae, using an emerging micro-NMR technology: high-resolution magic-angle coil spinning (HR-MACS. As a demonstrative study for whole cells, we perform two independent metabolomics studies identifying the significant metabolites associated with osmotic stress and aging.

Analytical methods in untargeted metabolomics: state of the art in 2015

Directory of Open Access Journals (Sweden)

Arnald eAlonso

2015-03-01

Full Text Available Metabolomics comprises the methods and techniques that are used to measure the small molecule composition of biofluids and tissues, and is actually one of the most rapidly evolving research fields. The determination of the metabolomic profile –the metabolome- has multiple applications in many biological sciences, including the developing of new diagnostic tools in medicine. Recent technological advances in nuclear magnetic resonance (NMR and mass spectrometry (MS are significantly improving our capacity to obtain more data from each biological sample. Consequently, there is a need for fast and accurate statistical and bioinformatic tools that can deal with the complexity and volume of the data generated in metabolomic studies. In this review we provide an update of the most commonly used analytical methods in metabolomics, starting from raw data processing and ending with pathway analysis and biomarker identification. Finally, the integration of metabolomic profiles with molecular data from other high throughput biotechnologies is also reviewed.

Certified Reference Material for Use in 1H, 31P, and 19F Quantitative NMR, Ensuring Traceability to the International System of Units.

Science.gov (United States)

Rigger, Romana; Rück, Alexander; Hellriegel, Christine; Sauermoser, Robert; Morf, Fabienne; Breitruck, KathrinBreitruck; Obkircher, Markus

2017-09-01

In recent years, quantitative NMR (qNMR) spectroscopy has become one of the most important tools for content determination of organic substances and quantitative evaluation of impurities. Using Certified Reference Materials (CRMs) as internal or external standards, the extensively used qNMR method can be applied for purity determination, including unbroken traceability to the International System of Units (SI). The implementation of qNMR toward new application fields, e.g., metabolomics, environmental analysis, and physiological pathway studies, brings along more complex molecules and systems, thus making use of 1H qNMR challenging. A smart workaround is possible by the use of other NMR active nuclei, namely 31P and 19F. This article presents the development of three classes of qNMR CRMs based on different NMR active nuclei (1H, 31P, and 19F), and the corresponding approaches to establish traceability to the SI through primary CRMs from the National Institute of Standards and Technology and the National Metrology Institute of Japan. These TraceCERT® qNMR CRMs are produced under ISO/IEC 17025 and ISO Guide 34 using high-performance qNMR.

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.

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.

Pasture Feeding Changes the Bovine Rumen and Milk Metabolome

Directory of Open Access Journals (Sweden)

Tom F. O’Callaghan

2018-04-01

. CLV feeding resulted in increased concentrations of milk urea. Milk from pasture-based feeding systems was shown to have significantly higher concentrations of hippuric acid, a potential biomarker of pasture-derived milk. This study has demonstrated that 1H-NMR metabolomics coupled with multivariate analysis is capable of distinguishing both rumen-fluid and milk derived from cows on different feeding systems, specifically between indoor TMR and pasture-based diets used in this study.

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

DEFF Research Database (Denmark)

Trimigno, Alessia

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

"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. • "1H 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

Metabolomics reveals the metabolic shifts following an intervention with rye bread in postmenopausal women- a randomized control trial

Directory of Open Access Journals (Sweden)

Moazzami Ali A

2012-10-01

Full Text Available Abstract Background Epidemiological studies have consistently shown that whole grain (WG cereals can protect against the development of chronic diseases, but the underlying mechanism is not fully understood. Among WG products, WG rye is considered even more potent because of its unique discrepancy in postprandial insulin and glucose responses known as the rye factor. In this study, an NMR-based metabolomics approach was applied to study the metabolic effects of WG rye as a tool to determine the beneficial effects of WG rye on human health. Methods Thirty-three postmenopausal Finnish women with elevated serum total cholesterol (5.0-8.5 mmol/L and BMI of 20–33 kg/m2 consumed a minimum of 20% of their daily energy intake as high fiber WG rye bread (RB or refined wheat bread (WB in a randomized, controlled, crossover design with two 8-wk intervention periods separated by an 8-wk washout period. At the end of each intervention period, fasting serum was collected for NMR-based metabolomics and the analysis of cholesterol fractions. Multilevel partial least squares discriminant analysis was used for paired comparisons of multivariate data. Results The metabolomics analysis of serum showed lower leucine and isoleucine and higher betaine and N,N-dimethylglycine levels after RB than WB intake. To further investigate the metabolic effects of RB, the serum cholesterol fractions were measured. Total- and LDL-cholesterol levels were higher after RB intake than after WB (p Conclusions This study revealed favorable shifts in branched amino acid and single carbon metabolism and an unfavorable shift in serum cholesterol levels after RB intake in postmenopausal women, which should be considered for evaluating health beneficial effects of rye products.

Metabolomic variation of brassica rapa var. rapa (var. raapstelen) and raphanus sativus l. at different developmental stages

International Nuclear Information System (INIS)

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

2014-01-01

Brassica rapa (var. raapstelen) and Raphanus sativus (red radish) are being used as food and fodder while also known as model in recent plant research due to the diversity of metabolites as well as genetic resemblance to Arabidopsis. This study explains the change in metabolites (amino acids, organic acids, chlorophyll, carotenoids, tocopherols, ascorbic acid, sucrose, phenylpropanoids and glucosinolates) during plant development. In present study the metabolomic variation in relation to plant growth has been evaluated, for Brassica rapa (var. raapstelen) and red radish (Raphanus sativus) at three different developmental stages. A non-targeted and targeted metabolomic approach by NMR and HPLC in combination with Principal component analysis (PCA) of the data was used to identify phytochemicals being influenced by plant growth. The results lead to the better understanding of metabolic changes during plant development and show the importance of plant age with respect to the metabolomic profile of vegetables. (author)

NMR-based metabolite profiling of human milk: A pilot study of methods for investigating compositional changes during lactation

International Nuclear Information System (INIS)

Wu, Junfang; Domellöf, Magnus; Zivkovic, Angela M.; Larsson, Göran; Öhman, Anders; Nording, Malin L.

2016-01-01

Low-molecular-weight metabolites in human milk are gaining increasing interest in studies of infant nutrition. In the present study, the milk metabolome from a single mother was explored at different stages of lactation. Metabolites were extracted from sample aliquots using either methanol/water (MeOH/H_2O) extraction or ultrafiltration. Nuclear magnetic resonance (NMR) spectroscopy was used for metabolite identification and quantification, and multi- and univariate statistical data analyses were used to detect changes over time of lactation. Compared to MeOH/H_2O extraction, ultrafiltration more efficiently reduced the interference from lipid and protein resonances, thereby enabling the identification and quantification of 36 metabolites. The human milk metabolomes at the early (9–24 days after delivery) and late (31–87 days after delivery) stages of lactation were distinctly different according to multi- and univariate statistics. The late lactation stage was characterized by significantly elevated concentrations of lactose, choline, alanine, glutamate, and glutamine, as well as by reduced levels of citrate, phosphocholine, glycerophosphocholine, and N-acetylglucosamine. Our results indicate that there are significant compositional changes of the human milk metabolome also in different phases of the matured lactation stage. These findings complement temporal studies on the colostrum and transitional metabolome in providing a better understanding of the nutritional variations received by an infant. - Highlights: • 36 metabolites were simultaneously quantified in human milk by NMR. • Ultrafiltration more efficiently reduces interferences than MeOH/H_2O extraction. • Compositional changes of the human milk exist during the matured lactation stage.

NMR-based metabolite profiling of human milk: A pilot study of methods for investigating compositional changes during lactation

Energy Technology Data Exchange (ETDEWEB)

Wu, Junfang [Department of Chemistry, Umeå University (Sweden); Domellöf, Magnus [Department of Clinical Sciences, Pediatrics, Umeå University (Sweden); Zivkovic, Angela M. [Foods for Health Institute, University of California, Davis, CA (United States); Department of Nutrition, University of California, Davis, CA (United States); Larsson, Göran [Department of Medical Biochemistry and Biophysics, Unit of Research, Education and Development-Östersund, Umeå University (Sweden); Öhman, Anders, E-mail: anders.ohman01@umu.se [Department of Pharmacology and Clinical Neuroscience, Umeå University (Sweden); Nording, Malin L., E-mail: malin.nording@umu.se [Department of Chemistry, Umeå University (Sweden)

2016-01-15

Low-molecular-weight metabolites in human milk are gaining increasing interest in studies of infant nutrition. In the present study, the milk metabolome from a single mother was explored at different stages of lactation. Metabolites were extracted from sample aliquots using either methanol/water (MeOH/H{sub 2}O) extraction or ultrafiltration. Nuclear magnetic resonance (NMR) spectroscopy was used for metabolite identification and quantification, and multi- and univariate statistical data analyses were used to detect changes over time of lactation. Compared to MeOH/H{sub 2}O extraction, ultrafiltration more efficiently reduced the interference from lipid and protein resonances, thereby enabling the identification and quantification of 36 metabolites. The human milk metabolomes at the early (9–24 days after delivery) and late (31–87 days after delivery) stages of lactation were distinctly different according to multi- and univariate statistics. The late lactation stage was characterized by significantly elevated concentrations of lactose, choline, alanine, glutamate, and glutamine, as well as by reduced levels of citrate, phosphocholine, glycerophosphocholine, and N-acetylglucosamine. Our results indicate that there are significant compositional changes of the human milk metabolome also in different phases of the matured lactation stage. These findings complement temporal studies on the colostrum and transitional metabolome in providing a better understanding of the nutritional variations received by an infant. - Highlights: • 36 metabolites were simultaneously quantified in human milk by NMR. • Ultrafiltration more efficiently reduces interferences than MeOH/H{sub 2}O extraction. • Compositional changes of the human milk exist during the matured lactation stage.

PGI chicory (Cichorium intybus L.) traceability by means of HRMAS-NMR spectroscopy: a preliminary study.

Science.gov (United States)

Ritota, Mena; Casciani, Lorena; Valentini, Massimiliano

2013-05-01

Analytical traceability of PGI and PDO foods (Protected Geographical Indication and Protected Denomination Origin respectively) is one of the most challenging tasks of current applied research. Here we proposed a metabolomic approach based on the combination of (1)H high-resolution magic angle spinning-nuclear magnetic resonance (HRMAS-NMR) spectroscopy with multivariate analysis, i.e. PLS-DA, as a reliable tool for the traceability of Italian PGI chicories (Cichorium intybus L.), i.e. Radicchio Rosso di Treviso and Radicchio Variegato di Castelfranco, also known as red and red-spotted, respectively. The metabolic profile was gained by means of HRMAS-NMR, and multivariate data analysis allowed us to build statistical models capable of providing clear discrimination among the two varieties and classification according to the geographical origin. Based on Variable Importance in Projection values, the molecular markers for classifying the different types of red chicories analysed were found accounting for both the cultivar and the place of origin. © 2012 Society of Chemical Industry.

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

1H nuclear magnetic resonance-based metabolomic characterization of wines by grape varieties and production areas.

Science.gov (United States)

Son, Hong-Seok; Kim, Ki Myong; van den Berg, Frans; Hwang, Geum-Sook; Park, Won-Mok; Lee, Cherl-Ho; Hong, Young-Shick

2008-09-10

(1)H NMR spectroscopy was used to investigate the metabolic differences in wines produced from different grape varieties and different regions. A significant separation among wines from Campbell Early, Cabernet Sauvignon, and Shiraz grapes was observed using principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). The metabolites contributing to the separation were assigned to be 2,3-butanediol, lactate, acetate, proline, succinate, malate, glycerol, tartarate, glucose, and phenolic compounds by PCA and PLS-DA loading plots. Wines produced from Cabernet Sauvignon grapes harvested in the continental areas of Australia, France, and California were also separated. PLS-DA loading plots revealed that the level of proline in Californian Cabernet Sauvignon wines was higher than that in Australian and French Cabernet Sauvignon, Australian Shiraz, and Korean Campbell Early wines, showing that the chemical composition of the grape berries varies with the variety and growing area. This study highlights the applicability of NMR-based metabolomics with multivariate statistical data sets in determining wine quality and product origin.

Livestock metabolomics and the livestock metabolome: A systematic review

Science.gov (United States)

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

2017-01-01

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

Livestock metabolomics and the livestock metabolome: A systematic review.

Science.gov (United States)

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

2017-01-01

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

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

Science.gov (United States)

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

2015-11-01

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

Challenges of metabolomics in human gut microbiota research.

Science.gov (United States)

Smirnov, Kirill S; Maier, Tanja V; Walker, Alesia; Heinzmann, Silke S; Forcisi, Sara; Martinez, Inés; Walter, Jens; Schmitt-Kopplin, Philippe

2016-08-01

The review highlights the role of metabolomics in studying human gut microbial metabolism. Microbial communities in our gut exert a multitude of functions with huge impact on human health and disease. Within the meta-omics discipline, gut microbiome is studied by (meta)genomics, (meta)transcriptomics, (meta)proteomics and metabolomics. The goal of metabolomics research applied to fecal samples is to perform their metabolic profiling, to quantify compounds and classes of interest, to characterize small molecules produced by gut microbes. Nuclear magnetic resonance spectroscopy and mass spectrometry are main technologies that are applied in fecal metabolomics. Metabolomics studies have been increasingly used in gut microbiota related research regarding health and disease with main focus on understanding inflammatory bowel diseases. The elucidated metabolites in this field are summarized in this review. We also addressed the main challenges of metabolomics in current and future gut microbiota research. The first challenge reflects the need of adequate analytical tools and pipelines, including sample handling, selection of appropriate equipment, and statistical evaluation to enable meaningful biological interpretation. The second challenge is related to the choice of the right animal model for studies on gut microbiota. We exemplified this using NMR spectroscopy for the investigation of cross-species comparison of fecal metabolite profiles. Finally, we present the problem of variability of human gut microbiota and metabolome that has important consequences on the concepts of personalized nutrition and medicine. Copyright © 2016 Elsevier GmbH. All rights reserved.

1H NMR metabolomics identification of markers of hypoxia-induced metabolic shifts in a breast cancer model system

International Nuclear Information System (INIS)

Weljie, Aalim M.; Bondareva, Alla; Zang, Ping; Jirik, Frank R.

2011-01-01

Hypoxia can promote invasive behavior in cancer cells and alters the response to therapeutic intervention as a result of changes in the expression many genes, including genes involved in intermediary metabolism. Although metabolomics technologies are capable of simultaneously measuring a wide range of metabolites in an untargeted manner, these methods have been relatively under utilized in the study of cancer cell responses to hypoxia. Thus, 1 H NMR metabolomics was used to examine the effects of hypoxia in the MDA-MB-231 human breast cancer cell line, both in vitro and in vivo. Cell cultures were compared with respect to their metabolic responses during growth under either hypoxic (1% O 2 ) or normoxic conditions. Orthogonal partial least squares discriminant analysis (OPLS-DA) was used to identify a set of metabolites that were responsive to hypoxia. Via intracardiac administration, MDA-MB-231 cells were also used to generate widespread metastatic disease in immuno-compromised mice. Serum metabolite analysis was conducted to compare animals with and without a large tumor burden. Intriguingly, using a cross-plot of the OPLS loadings, both the in vitro and in vivo samples yielded a subset of metabolites that were significantly altered by hypoxia. These included primarily energy metabolites and amino acids, indicative of known alterations in energy metabolism, and possibly protein synthesis or catabolism. The results suggest that the metabolite pattern identified might prove useful as a marker for intra-tumoral hypoxia.

MetAssimulo:Simulation of Realistic NMR Metabolic Profiles

Directory of Open Access Journals (Sweden)

De Iorio Maria

2010-10-01

Full Text Available Abstract Background Probing the complex fusion of genetic and environmental interactions, metabolic profiling (or metabolomics/metabonomics, the study of small molecules involved in metabolic reactions, is a rapidly expanding 'omics' field. A major technique for capturing metabolite data is 1H-NMR spectroscopy and this yields highly complex profiles that require sophisticated statistical analysis methods. However, experimental data is difficult to control and expensive to obtain. Thus data simulation is a productive route to aid algorithm development. Results MetAssimulo is a MATLAB-based package that has been developed to simulate 1H-NMR spectra of complex mixtures such as metabolic profiles. Drawing data from a metabolite standard spectral database in conjunction with concentration information input by the user or constructed automatically from the Human Metabolome Database, MetAssimulo is able to create realistic metabolic profiles containing large numbers of metabolites with a range of user-defined properties. Current features include the simulation of two groups ('case' and 'control' specified by means and standard deviations of concentrations for each metabolite. The software enables addition of spectral noise with a realistic autocorrelation structure at user controllable levels. A crucial feature of the algorithm is its ability to simulate both intra- and inter-metabolite correlations, the analysis of which is fundamental to many techniques in the field. Further, MetAssimulo is able to simulate shifts in NMR peak positions that result from matrix effects such as pH differences which are often observed in metabolic NMR spectra and pose serious challenges for statistical algorithms. Conclusions No other software is currently able to simulate NMR metabolic profiles with such complexity and flexibility. This paper describes the algorithm behind MetAssimulo and demonstrates how it can be used to simulate realistic NMR metabolic profiles with

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

Science.gov (United States)

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

2013-09-01

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

Phenotyping of Chronic Obstructive Pulmonary Disease Based on the Integration of Metabolomes and Clinical Characteristics

Directory of Open Access Journals (Sweden)

Kalle Kilk

2018-02-01

Full Text Available Apart from the refined management-oriented clinical stratification of chronic obstructive pulmonary disease (COPD, the molecular pathologies behind this highly prevalent disease have remained obscure. The aim of this study was the characterization of patients with COPD, based on the metabolomic profiling of peripheral blood and exhaled breath condensate (EBC within the context of defined clinical and demographic variables. Mass-spectrometry-based targeted analysis of serum metabolites (mainly amino acids and lipid species, untargeted profiles of serum and EBC of patients with COPD of different clinical characteristics (n = 25 and control individuals (n = 21 were performed. From the combined clinical/demographic and metabolomics data, associations between clinical/demographic and metabolic parameters were searched and a de novo phenotyping for COPD was attempted. Adjoining the clinical parameters, sphingomyelins were the best to differentiate COPD patients from controls. Unsaturated fatty acid-containing lipids, ornithine metabolism and plasma protein composition-associated signals from the untargeted analysis differentiated the Global Initiative for COPD (GOLD categories. Hierarchical clustering did not reveal a clinical-metabolomic stratification superior to the strata set by the GOLD consensus. We conclude that while metabolomics approaches are good for finding biomarkers and clarifying the mechanism of the disease, there are no distinct co-variate independent clinical-metabolic phenotypes.

Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis.

Science.gov (United States)

Xia, Jianguo; Wishart, David S

2016-09-07

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

{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

Metabolomics for laboratory diagnostics.

Science.gov (United States)

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

2015-09-10

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

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

International Nuclear Information System (INIS)

Elmsjö, Albert; Haglöf, Jakob; Engskog, Mikael K.R.; Nestor, Marika; Arvidsson, Torbjörn; Pettersson, Curt

2017-01-01

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

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. �

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...

1H-NMR-based metabolic analysis of human serum reveals novel markers of myocardial energy expenditure in heart failure patients.

Directory of Open Access Journals (Sweden)

Zhiyong Du

Full Text Available OBJECTIVE: Elevated myocardial energy expenditure (MEE is related with reduced left ventricular ejection fraction, and has also been documented as an independent predictor of cardiovascular mortality. However, the serum small-molecule metabolite profiles and pathophysiological mechanisms of elevated MEE in heart failure (HF are still lacking. Herein, we used 1H-NMR-based metabolomics analysis to screen for potential biomarkers of MEE in HF. METHODS: A total of 61 subjects were enrolled, including 46 patients with heart failure and 15 age-matched controls. Venous serum samples were collected from subjects after an 8-hour fast. An INOVA 600 MHz nuclear magnetic resonance spectrometer with Carr-Purcell-Melboom-Gill (CPMG pulse sequence was employed for the metabolomics analysis and MEE was calculated using colored Doppler echocardiography. Metabolomics data were processed using orthogonal signal correction and regression analysis was performed using the partial least squares method. RESULTS: The mean MEE levels of HF patients and controls were 139.61±58.18 cal/min and 61.09±23.54 cal/min, respectively. Serum metabolomics varied with MEE changed, and 3-hydroxybutyrate, acetone and succinate were significantly elevated with the increasing MEE. Importantly, these three metabolites were independent of administration of angiotensin converting enzyme inhibitor, β-receptor blockers, diuretics and statins (P>0.05. CONCLUSIONS: These results suggested that in patients with heart failure, MEE elevation was associated with significant changes in serum metabolomics profiles, especially the concentration of 3-hydroxybutyrate, acetone and succinate. These compounds could be used as potential serum biomarkers to study myocardial energy mechanism in HF patients.

Emerging New Strategies for Successful Metabolite Identification in Metabolomics

Energy Technology Data Exchange (ETDEWEB)

Bingol, Ahmet K.; Bruschweiler-Li, Lei; Li, Dawei; Zhang, Bo; Xie, Mouzhe; Bruschweiler, Rafael

2016-02-26

NMR is a very powerful tool for the identification of known and unknown (or unnamed) metabolites in complex mixtures as encountered in metabolomics. Known compounds can be reliably identified using 2D NMR methods, such as 13C-1H HSQC, for which powerful web servers with databases are available for semi-automated analysis. For the identification of unknown compounds, new combinations of NMR with MS have been developed recently that make synergistic use of the mutual strengths of the two techniques. The use of chemical additives to the NMR tube, such as reactive agents, paramagnetic ions, or charged silica nanoparticles, permit the identification of metabolites with specific physical chemical properties. In the following sections, we give an overview of some of the recent advances in metabolite identification and discuss remaining challenges.

GC-MS-Based Metabolome and Metabolite Regulation in Serum-Resistant Streptococcus agalactiae.

Science.gov (United States)

Wang, Zhe; Li, Min-Yi; Peng, Bo; Cheng, Zhi-Xue; Li, Hui; Peng, Xuan-Xian

2016-07-01

Streptococcus agalactiae causes severe systemic infections in human and fish. In the present study, we established a pathogen-plasma interaction model by which we explored how S. agalactiae evaded serum-mediated killing. We found that S. agalactiae grew faster in the presence of yellow grouper plasma than in the absence of the plasma, indicating S. agalactiae evolved a way of evading the fish immune system. To determine the events underlying this phenotype, we applied GC-MS-based metabolomics approaches to identify differential metabolomes between S. agalactiae cultured with and without yellow grouper plasma. Through bioinformatics analysis, decreased malic acid and increased adenosine were identified as the most crucial metabolites that distinguish the two groups. Meanwhile, they presented with decreased TCA cycle and elevated purine metabolism, respectively. Finally, exogenous malic acid and adenosine were used to reprogram the plasma-resistant metabolome, leading to elevated and decreased susceptibility to the plasma, respectively. Therefore, our findings reveal for the first time that S. agalactiae utilizes a metabolic trick to respond to plasma killing as a result of serum resistance, which may be reverted or enhanced by exogenous malic acid and adenosine, respectively, suggesting that the metabolic trick can be regulated by metabolites.

Application of Metabolomics in Thyroid Cancer Research

Directory of Open Access Journals (Sweden)

Anna Wojakowska

2015-01-01

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

Use of optimized 1D TOCSY NMR for improved quantitation and metabolomic analysis of biofluids

Energy Technology Data Exchange (ETDEWEB)

Sandusky, Peter [Eckerd College, Department of Chemistry (United States); Appiah-Amponsah, Emmanuel; Raftery, Daniel, E-mail: raftery@purdue.edu [Purdue University, Department of Chemistry (United States)

2011-04-15

One dimensional selective TOCSY experiments have been shown to be advantageous in providing improved data inputs for principle component analysis (PCA) (Sandusky and Raftery 2005a, b). Better subpopulation cluster resolution in the observed scores plots results from the ability to isolate metabolite signals of interest via the TOCSY based filtering approach. This report reexamines the quantitative aspects of this approach, first by optimizing the 1D TOCSY experiment as it relates to the measurement of biofluid constituent concentrations, and second by comparing the integration of 1D TOCSY read peaks to the bucket integration of 1D proton NMR spectra in terms of precision and accuracy. This comparison indicates that, because of the extensive peak overlap that occurs in the 1D proton NMR spectra of biofluid samples, bucket integrals are often far less accurate as measures of individual constituent concentrations than 1D TOCSY read peaks. Even spectral fitting approaches have proven difficult in the analysis of significantly overlapped spectral regions. Measurements of endogenous taurine made over a sample population of human urine demonstrates that, due to background signals from other constituents, bucket integrals of 1D proton spectra routinely overestimate the taurine concentrations and distort its variation over the sample population. As a result, PCA calculations performed using data matrices incorporating 1D TOCSY determined taurine concentrations produce better scores plot subpopulation cluster resolution.

Use of optimized 1D TOCSY NMR for improved quantitation and metabolomic analysis of biofluids

International Nuclear Information System (INIS)

Sandusky, Peter; Appiah-Amponsah, Emmanuel; Raftery, Daniel

2011-01-01

One dimensional selective TOCSY experiments have been shown to be advantageous in providing improved data inputs for principle component analysis (PCA) (Sandusky and Raftery 2005a, b). Better subpopulation cluster resolution in the observed scores plots results from the ability to isolate metabolite signals of interest via the TOCSY based filtering approach. This report reexamines the quantitative aspects of this approach, first by optimizing the 1D TOCSY experiment as it relates to the measurement of biofluid constituent concentrations, and second by comparing the integration of 1D TOCSY read peaks to the bucket integration of 1D proton NMR spectra in terms of precision and accuracy. This comparison indicates that, because of the extensive peak overlap that occurs in the 1D proton NMR spectra of biofluid samples, bucket integrals are often far less accurate as measures of individual constituent concentrations than 1D TOCSY read peaks. Even spectral fitting approaches have proven difficult in the analysis of significantly overlapped spectral regions. Measurements of endogenous taurine made over a sample population of human urine demonstrates that, due to background signals from other constituents, bucket integrals of 1D proton spectra routinely overestimate the taurine concentrations and distort its variation over the sample population. As a result, PCA calculations performed using data matrices incorporating 1D TOCSY determined taurine concentrations produce better scores plot subpopulation cluster resolution.

Metabolomic Tools to Assess the Chemistry and Bioactivity of Endophytic Aspergillus Strain.

Science.gov (United States)

Tawfike, Ahmed F; Tate, Rothwelle; Abbott, Gráinne; Young, Louise; Viegelmann, Christina; Schumacher, Marc; Diederich, Marc; Edrada-Ebel, RuAngelie

2017-10-01

Endophytic fungi associated with medicinal plants are a potential source of novel chemistry and biology that may find applications as pharmaceutical and agrochemical drugs. In this study, a combination of metabolomics and bioactivity-guided approaches were employed to isolate secondary metabolites with cytotoxicity against cancer cells from an endophytic Aspergillus aculeatus. The endophyte was isolated from the Egyptian medicinal plant Terminalia laxiflora and identified using molecular biological methods. Metabolomics and dereplication studies were accomplished by utilizing the MZmine software coupled with the universal Dictionary of Natural Products database. Metabolic profiling, with aid of multivariate data analysis, was performed at different stages of the growth curve to choose the optimized method suitable for up-scaling. The optimized culture method yielded a crude extract abundant with biologically-active secondary metabolites. Crude extracts were fractionated using different high-throughput chromatographic techniques. Purified compounds were identified by HR-ESI-MS, 1D- and 2D-NMR. This study introduced a new method of dereplication utilizing both high-resolution mass spectrometry and NMR spectroscopy. The metabolites were putatively identified by applying a chemotaxonomic filter. We also present a short review on the diverse chemistry of terrestrial endophytic strains of Aspergillus, which has become a part of our dereplication work and this will be of wide interest to those working in this field. © 2017 Wiley-VHCA AG, Zurich, Switzerland.

Evolution of the metabolome in response to selection for increased immunity in populations of Drosophila melanogaster.

Science.gov (United States)

Gogna, Navdeep; Sharma, Rakesh; Gupta, Vanika; Dorai, Kavita; Prasad, N G

2017-01-01

We used NMR-based metabolomics to test two hypotheses-(i) there will be evolved differences in the metabolome of selected and control populations even under un-infected conditions and (ii) post infection, the metabolomes of the selected and control populations will respond differently. We selected replicate populations of Drosophila melanogaster for increased survivorship (I) against a gram-negative pathogen. We subjected the selected (I) and their control populations (S) to three different treatments: (1) infected with heat-killed bacteria (i), (2) sham infected (s), and (3) untreated (u). We performed 1D and 2D NMR experiments to identify the metabolic differences. Multivariate analysis of the metabolic profiles of the untreated (Iu and Su) flies yielded higher concentrations of lipids, organic acids, sugars, amino acids, NAD and AMP in the Iu treatment as compared to the Su treatment, showing that even in the absence of infection, the metabolome of the I and S regimes was different. In the S and I regimes, post infection/injury, concentration of metabolites directly or indirectly associated with energy related pathways (lipids, organic acids, sugars) declined while the concentration of metabolites that are probably associated with immune response (amino acids) increased. However, in most cases, the I regime flies had a higher concentration of such metabolites even under un-infected conditions. The change in the metabolite concentration upon infection/injury was not always comparable between I and S regimes (in case of lactate, alanine, leucine, lysine, threonine) indicating that the I and S regimes had evolved to respond differentially to infection and to injury.

NMR-based metabonomic study of the sub-acute toxicity of titanium dioxide nanoparticles in rats after oral administration

Science.gov (United States)

Bu, Qian; Yan, Guangyan; Deng, Pengchi; Peng, Feng; Lin, Hongjun; Xu, Youzhi; Cao, Zhixing; Zhou, Tian; Xue, Aiqin; Wang, Yanli; Cen, Xiaobo; Zhao, Ying-Lan

2010-03-01

As titanium dioxide nanoparticles (TiO2 NPs) are widely used commercially, their potential toxicity on human health has attracted particular attention. In the present study, the oral toxicological effects of TiO2 NPs (dosed at 0.16, 0.4 and 1 g kg - 1, respectively) were investigated using conventional approaches and metabonomic analysis in Wistar rats. Serum chemistry, hematology and histopathology examinations were performed. The urine and serum were investigated by 1H nuclear magnetic resonance (NMR) using principal components and partial least squares discriminant analysis. The metabolic signature of urinalysis in TiO2 NP-treated rats showed increases in the levels of taurine, citrate, hippurate, histidine, trimethylamine-N-oxide (TMAO), citrulline, α-ketoglutarate, phenylacetylglycine (PAG) and acetate; moreover, decreases in the levels of lactate, betaine, methionine, threonine, pyruvate, 3-D-hydroxybutyrate (3-D-HB), choline and leucine were observed. The metabonomics analysis of serum showed increases in TMAO, choline, creatine, phosphocholine and 3-D-HB as well as decreases in glutamine, pyruvate, glutamate, acetoacetate, glutathione and methionine after TiO2 NP treatment. Aspartate aminotransferase (AST), creatine kinase (CK) and lactate dehydrogenase (LDH) were elevated and mitochondrial swelling in heart tissue was observed in TiO2 NP-treated rats. These findings indicate that disturbances in energy and amino acid metabolism and the gut microflora environment may be attributable to the slight injury to the liver and heart caused by TiO2 NPs. Moreover, the NMR-based metabolomic approach is a reliable and sensitive method to study the biochemical effects of nanomaterials.

NMR-based metabonomic study of the sub-acute toxicity of titanium dioxide nanoparticles in rats after oral administration

International Nuclear Information System (INIS)

Bu Qian; Lin Hongjun; Xu Youzhi; Cao Zhixing; Zhou Tian; Zhao Yinglan; Yan Guangyan; Cen Xiaobo; Deng Pengchi; Peng Feng; Xue Aiqin; Wang Yanli

2010-01-01

As titanium dioxide nanoparticles (TiO 2 NPs) are widely used commercially, their potential toxicity on human health has attracted particular attention. In the present study, the oral toxicological effects of TiO 2 NPs (dosed at 0.16, 0.4 and 1 g kg -1 , respectively) were investigated using conventional approaches and metabonomic analysis in Wistar rats. Serum chemistry, hematology and histopathology examinations were performed. The urine and serum were investigated by 1 H nuclear magnetic resonance (NMR) using principal components and partial least squares discriminant analysis. The metabolic signature of urinalysis in TiO 2 NP-treated rats showed increases in the levels of taurine, citrate, hippurate, histidine, trimethylamine-N-oxide (TMAO), citrulline, α-ketoglutarate, phenylacetylglycine (PAG) and acetate; moreover, decreases in the levels of lactate, betaine, methionine, threonine, pyruvate, 3-D-hydroxybutyrate (3-D-HB), choline and leucine were observed. The metabonomics analysis of serum showed increases in TMAO, choline, creatine, phosphocholine and 3-D-HB as well as decreases in glutamine, pyruvate, glutamate, acetoacetate, glutathione and methionine after TiO 2 NP treatment. Aspartate aminotransferase (AST), creatine kinase (CK) and lactate dehydrogenase (LDH) were elevated and mitochondrial swelling in heart tissue was observed in TiO 2 NP-treated rats. These findings indicate that disturbances in energy and amino acid metabolism and the gut microflora environment may be attributable to the slight injury to the liver and heart caused by TiO 2 NPs. Moreover, the NMR-based metabolomic approach is a reliable and sensitive method to study the biochemical effects of nanomaterials.

Pre-analytical method for NMR-based grape metabolic fingerprinting and chemometrics.

Science.gov (United States)

Ali, Kashif; Maltese, Federica; Fortes, Ana Margarida; Pais, Maria Salomé; Verpoorte, Robert; Choi, Young Hae

2011-10-10

Although metabolomics aims at profiling all the metabolites in organisms, data quality is quite dependent on the pre-analytical methods employed. In order to evaluate current methods, different pre-analytical methods were compared and used for the metabolic profiling of grapevine as a model plant. Five grape cultivars from Portugal in combination with chemometrics were analyzed in this study. A common extraction method with deuterated water and methanol was found effective in the case of amino acids, organic acids, and sugars. For secondary metabolites like phenolics, solid phase extraction with C-18 cartridges showed good results. Principal component analysis, in combination with NMR spectroscopy, was applied and showed clear distinction among the cultivars. Primary metabolites such as choline, sucrose, and leucine were found discriminating for 'Alvarinho', while elevated levels of alanine, valine, and acetate were found in 'Arinto' (white varieties). Among the red cultivars, higher signals for citrate and GABA in 'Touriga Nacional', succinate and fumarate in 'Aragonês', and malate, ascorbate, fructose and glucose in 'Trincadeira', were observed. Based on the phenolic profile, 'Arinto' was found with higher levels of phenolics as compared to 'Alvarinho'. 'Trincadeira' showed lowest phenolics content while higher levels of flavonoids and phenylpropanoids were found in 'Aragonês' and 'Touriga Nacional', respectively. It is shown that the metabolite composition of the extract is highly affected by the extraction procedure and this consideration has to be taken in account for metabolomics studies. Copyright © 2011 Elsevier B.V. All rights reserved.

Data fusion in metabolomic cancer diagnostics

DEFF Research Database (Denmark)

Bro, Rasmus; Nielsen, Hans Jørgen; Savorani, Francesco

2013-01-01

We have recently shown that fluorescence spectroscopy of plasma samples has promising abilities regarding early detection of colorectal cancer. In the present paper, these results were further developed by combining fluorescence with the biomarkers, CEA and TIMP-1 and traditional metabolomic meas...... measurements in the form of (1)H NMR spectroscopy. The results indicate that using an extensive profile established by combining such measurements together with the biomarkers is better than using single markers....

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 UTI caused by Escherichia coli and healthy controls. Acetate and trimethylamine were identified as discriminant metabolites. The concentrations of both metabolites were calculated and used to build the ROC curves. The discriminant metabolites identified were also evaluated in urine samples from patients with other pathogens 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.

Fragment based drug discovery: practical implementation based on ¹⁹F NMR spectroscopy.

Science.gov (United States)

Jordan, John B; Poppe, Leszek; Xia, Xiaoyang; Cheng, Alan C; Sun, Yax; Michelsen, Klaus; Eastwood, Heather; Schnier, Paul D; Nixey, Thomas; Zhong, Wenge

2012-01-26

Fragment based drug discovery (FBDD) is a widely used tool for discovering novel therapeutics. NMR is a powerful means for implementing FBDD, and several approaches have been proposed utilizing (1)H-(15)N heteronuclear single quantum coherence (HSQC) as well as one-dimensional (1)H and (19)F NMR to screen compound mixtures against a target of interest. While proton-based NMR methods of fragment screening (FBS) have been well documented and are widely used, the use of (19)F detection in FBS has been only recently introduced (Vulpetti et al. J. Am. Chem. Soc.2009, 131 (36), 12949-12959) with the aim of targeting "fluorophilic" sites in proteins. Here, we demonstrate a more general use of (19)F NMR-based fragment screening in several areas: as a key tool for rapid and sensitive detection of fragment hits, as a method for the rapid development of structure-activity relationship (SAR) on the hit-to-lead path using in-house libraries and/or commercially available compounds, and as a quick and efficient means of assessing target druggability.

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.

Citrus Quality Control: An NMR/MRI Problem-Based Experiment

Science.gov (United States)

Erhart, Sarah E.; McCarrick, Robert M.; Lorigan, Gary A.; Yezierski, Ellen J.

2016-01-01

An experiment seated in an industrial context can provide an engaging framework and unique learning opportunity for an upper-division physical chemistry laboratory. An experiment that teaches NMR/MRI through a problem-based quality control of citrus products was developed. In this experiment, using a problem-based learning (PBL) approach, students…

Nutritional Metabolomics

DEFF Research Database (Denmark)

Gürdeniz, Gözde

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

NMR data-driven structure determination using NMR-I-TASSER in the CASD-NMR experiment

Energy Technology Data Exchange (ETDEWEB)

Jang, Richard [Huazhong University of Science and Technology, School of Software Engineering (China); Wang, Yan [Huazhong University of Science and Technology, School of Life Science and Technology (China); Xue, Zhidong, E-mail: zdxue@hust.edu.cn [Huazhong University of Science and Technology, School of Software Engineering (China); Zhang, Yang, E-mail: zhng@umich.edu [University of Michigan, Department of Computational Medicine and Bioinformatics (United States)

2015-08-15

NMR-I-TASSER, an adaption of the I-TASSER algorithm combining NMR data for protein structure determination, recently joined the second round of the CASD-NMR experiment. Unlike many molecular dynamics-based methods, NMR-I-TASSER takes a molecular replacement-like approach to the problem by first threading the target through the PDB to identify structural templates which are then used for iterative NOE assignments and fragment structure assembly refinements. The employment of multiple templates allows NMR-I-TASSER to sample different topologies while convergence to a single structure is not required. Retroactive and blind tests of the CASD-NMR targets from Rounds 1 and 2 demonstrate that even without using NOE peak lists I-TASSER can generate correct structure topology with 15 of 20 targets having a TM-score above 0.5. With the addition of NOE-based distance restraints, NMR-I-TASSER significantly improved the I-TASSER models with all models having the TM-score above 0.5. The average RMSD was reduced from 5.29 to 2.14 Å in Round 1 and 3.18 to 1.71 Å in Round 2. There is no obvious difference in the modeling results with using raw and refined peak lists, indicating robustness of the pipeline to the NOE assignment errors. Overall, despite the low-resolution modeling the current NMR-I-TASSER pipeline provides a coarse-grained structure folding approach complementary to traditional molecular dynamics simulations, which can produce fast near-native frameworks for atomic-level structural refinement.

Metabolomics and Personalized Medicine.

Science.gov (United States)

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

2016-01-01

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

NMR-Based Identification of Metabolites in Polar and Non-Polar Extracts of Avian Liver.

Science.gov (United States)

Fathi, Fariba; Brun, Antonio; Rott, Katherine H; Falco Cobra, Paulo; Tonelli, Marco; Eghbalnia, Hamid R; Caviedes-Vidal, Enrique; Karasov, William H; Markley, John L

2017-11-16

Metabolites present in liver provide important clues regarding the physiological state of an organism. The aim of this work was to evaluate a protocol for high-throughput NMR-based analysis of polar and non-polar metabolites from a small quantity of liver tissue. We extracted the tissue with a methanol/chloroform/water mixture and isolated the polar metabolites from the methanol/water layer and the non-polar metabolites from the chloroform layer. Following drying, we re-solubilized the fractions for analysis with a 600 MHz NMR spectrometer equipped with a 1.7 mm cryogenic probe. In order to evaluate the feasibility of this protocol for metabolomics studies, we analyzed the metabolic profile of livers from house sparrow ( Passer domesticus ) nestlings raised on two different diets: livers from 10 nestlings raised on a high protein diet (HP) for 4 d and livers from 12 nestlings raised on the HP diet for 3 d and then switched to a high carbohydrate diet (HC) for 1 d. The protocol enabled the detection of 52 polar and nine non-polar metabolites in ¹H NMR spectra of the extracts. We analyzed the lipophilic metabolites by one-way ANOVA to assess statistically significant concentration differences between the two groups. The results of our studies demonstrate that the protocol described here can be exploited for high-throughput screening of small quantities of liver tissue (approx. 100 mg wet mass) obtainable from small animals.

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

Directory of Open Access Journals (Sweden)

Maria P. H. Koster

2015-01-01

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

Two approaches to 3D reconstruction in NMR zeugmatography

International Nuclear Information System (INIS)

Marr, R.B.; Chen, C.N.; Lauterbur, P.C.

1980-01-01

In nuclear magnetic resonance (NMR) zeugmatography, the primary data pertain to integrals of the unknown nuclear spin density f(x,y,z) over planes instead of lines in R 3 . Two natural approaches to reconstructing f from such data are: (1) By numerical implementation of the inverse Radon transform in three dimensions (the direct approach), and (2) by application, in two successive stages, of existing well-known algorithms for inverting the two-dimensional Radon transform (the two-stage approach). These two approaches are discussed and compared, both from a theoretical standpoint and through computer results obtained with real NMR data. For the cases studied to date the two methods appear to produce qualitatively similar results

NMR-based metabonomic study of the sub-acute toxicity of titanium dioxide nanoparticles in rats after oral administration

Energy Technology Data Exchange (ETDEWEB)

Bu Qian; Lin Hongjun; Xu Youzhi; Cao Zhixing; Zhou Tian; Zhao Yinglan [State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, West China Medical School, Sichuan University, Chengdu 610041 (China); Yan Guangyan; Cen Xiaobo [National Chengdu Center for Safety Evaluation of Drugs, State Key Laboratory of Biotherapy, West China Hospital, West China Medical School, Sichuan University, Chengdu 610041 (China); Deng Pengchi [Analytical and Testing Center, Sichuan University, Chengdu 610041 (China); Peng Feng [Department of Thoracic Oncology of Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, West China Medical School, Sichuan University, Chengdu 610041 (China); Xue Aiqin [Institute of Bioengineering, Zhejiang Sci-Tech University Road 2, Xiasha, Hangzhou 310018 (China); Wang Yanli, E-mail: alancenxb@sina.com [Tianjin Children' s Hospital, Tianjin 300074 (China)

2010-03-26

As titanium dioxide nanoparticles (TiO{sub 2} NPs) are widely used commercially, their potential toxicity on human health has attracted particular attention. In the present study, the oral toxicological effects of TiO{sub 2} NPs (dosed at 0.16, 0.4 and 1 g kg{sup -1}, respectively) were investigated using conventional approaches and metabonomic analysis in Wistar rats. Serum chemistry, hematology and histopathology examinations were performed. The urine and serum were investigated by {sup 1}H nuclear magnetic resonance (NMR) using principal components and partial least squares discriminant analysis. The metabolic signature of urinalysis in TiO{sub 2} NP-treated rats showed increases in the levels of taurine, citrate, hippurate, histidine, trimethylamine-N-oxide (TMAO), citrulline, {alpha}-ketoglutarate, phenylacetylglycine (PAG) and acetate; moreover, decreases in the levels of lactate, betaine, methionine, threonine, pyruvate, 3-D-hydroxybutyrate (3-D-HB), choline and leucine were observed. The metabonomics analysis of serum showed increases in TMAO, choline, creatine, phosphocholine and 3-D-HB as well as decreases in glutamine, pyruvate, glutamate, acetoacetate, glutathione and methionine after TiO{sub 2} NP treatment. Aspartate aminotransferase (AST), creatine kinase (CK) and lactate dehydrogenase (LDH) were elevated and mitochondrial swelling in heart tissue was observed in TiO{sub 2} NP-treated rats. These findings indicate that disturbances in energy and amino acid metabolism and the gut microflora environment may be attributable to the slight injury to the liver and heart caused by TiO{sub 2} NPs. Moreover, the NMR-based metabolomic approach is a reliable and sensitive method to study the biochemical effects of nanomaterials.

Solution NMR Spectroscopy in Target-Based Drug Discovery.

Science.gov (United States)

Li, Yan; Kang, Congbao

2017-08-23

Solution NMR spectroscopy is a powerful tool to study protein structures and dynamics under physiological conditions. This technique is particularly useful in target-based drug discovery projects as it provides protein-ligand binding information in solution. Accumulated studies have shown that NMR will play more and more important roles in multiple steps of the drug discovery process. In a fragment-based drug discovery process, ligand-observed and protein-observed NMR spectroscopy can be applied to screen fragments with low binding affinities. The screened fragments can be further optimized into drug-like molecules. In combination with other biophysical techniques, NMR will guide structure-based drug discovery. In this review, we describe the possible roles of NMR spectroscopy in drug discovery. We also illustrate the challenges encountered in the drug discovery process. We include several examples demonstrating the roles of NMR in target-based drug discoveries such as hit identification, ranking ligand binding affinities, and mapping the ligand binding site. We also speculate the possible roles of NMR in target engagement based on recent processes in in-cell NMR spectroscopy.

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

Science.gov (United States)

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

2014-09-01

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

Unraveling the concentration-dependent metabolic response of Pseudomonas sp. HF-1 to nicotine stress by ¹H NMR-based metabolomics.

Science.gov (United States)

Ye, Yangfang; Wang, Xin; Zhang, Limin; Lu, Zhenmei; Yan, Xiaojun

2012-07-01

Nicotine can cause oxidative damage to organisms; however, some bacteria, for example Pseudomonas sp. HF-1, are resistant to such oxidative stress. In the present study, we analyzed the concentration-dependent metabolic response of Pseudomonas sp. HF-1 to nicotine stress using ¹H NMR spectroscopy coupled with multivariate data analysis. We found that the dominant metabolites in Pseudomonas sp. HF-1 were eight aliphatic organic acids, six amino acids, three sugars and 11 nucleotides. After 18 h of cultivation, 1 g/L nicotine caused significant elevation of sugar (glucose, trehalose and maltose), succinate and nucleic acid metabolites (cytidine, 5'-CMP, guanine 2',3'-cyclic phosphate and adenosine 2',3'-cyclic phosphate), but decrease of glutamate, putrescine, pyrimidine, 2-propanol, diethyl ether and acetamide levels. Similar metabolomic changes were induced by 2 g/L nicotine, except that no significant change in trehalose, 5'-UMP levels and diethyl ether were found. However, 3 g/L nicotine led to a significant elevation in the two sugars (trehalose and maltose) levels and decrease in the levels of glutamate, putrescine, pyrimidine and 2-propanol. Our findings indicated that nicotine resulted in the enhanced nucleotide biosynthesis, decreased glucose catabolism, elevated succinate accumulation, severe disturbance in osmoregulation and complex antioxidant strategy. And a further increase of nicotine level was a critical threshold value that triggered the change of metabolic flow in Pseudomonas sp. HF-1. These findings revealed the comprehensive insights into the metabolic response of nicotine-degrading bacteria to nicotine-induced oxidative toxicity.

Metabolomics: A Primer.

Science.gov (United States)

Liu, Xiaojing; Locasale, Jason W

2017-04-01

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

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

Science.gov (United States)

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

2018-04-06

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

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.

Advances in high-resolution mass spectrometry based on metabolomics studies for food--a review.

Science.gov (United States)

Rubert, Josep; Zachariasova, Milena; Hajslova, Jana

2015-01-01

Food authenticity becomes a necessity for global food policies, since food placed in the market without fail has to be authentic. It has always been a challenge, since in the past minor components, called also markers, have been mainly monitored by chromatographic methods in order to authenticate the food. Nevertheless, nowadays, advanced analytical methods have allowed food fingerprints to be achieved. At the same time they have been also combined with chemometrics, which uses statistical methods in order to verify food and to provide maximum information by analysing chemical data. These sophisticated methods based on different separation techniques or stand alone have been recently coupled to high-resolution mass spectrometry (HRMS) in order to verify the authenticity of food. The new generation of HRMS detectors have experienced significant advances in resolving power, sensitivity, robustness, extended dynamic range, easier mass calibration and tandem mass capabilities, making HRMS more attractive and useful to the food metabolomics community, therefore becoming a reliable tool for food authenticity. The purpose of this review is to summarise and describe the most recent metabolomics approaches in the area of food metabolomics, and to discuss the strengths and drawbacks of the HRMS analytical platforms combined with chemometrics.

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

Energy Technology Data Exchange (ETDEWEB)

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

2016-02-16

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

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

NMR approaches in structure-based lead discovery: recent developments and new frontiers for targeting multi-protein complexes.

Science.gov (United States)

Dias, David M; Ciulli, Alessio

2014-01-01

Nuclear magnetic resonance (NMR) spectroscopy is a pivotal method for structure-based and fragment-based lead discovery because it is one of the most robust techniques to provide information on protein structure, dynamics and interaction at an atomic level in solution. Nowadays, in most ligand screening cascades, NMR-based methods are applied to identify and structurally validate small molecule binding. These can be high-throughput and are often used synergistically with other biophysical assays. Here, we describe current state-of-the-art in the portfolio of available NMR-based experiments that are used to aid early-stage lead discovery. We then focus on multi-protein complexes as targets and how NMR spectroscopy allows studying of interactions within the high molecular weight assemblies that make up a vast fraction of the yet untargeted proteome. Finally, we give our perspective on how currently available methods could build an improved strategy for drug discovery against such challenging targets. Copyright © 2014 The Authors. Published by Elsevier Ltd.. All rights reserved.

Application of Metabolomics to Quality Control of Natural Product Derived Medicines.

Science.gov (United States)

Lee, Kyung-Min; Jeon, Jun-Yeong; Lee, Byeong-Ju; Lee, Hwanhui; Choi, Hyung-Kyoon

2017-11-01

Metabolomics has been used as a powerful tool for the analysis and quality assessment of the natural product (NP)-derived medicines. It is increasingly being used in the quality control and standardization of NP-derived medicines because they are composed of hundreds of natural compounds. The most common techniques that are used in metabolomics consist of NMR, GC-MS, and LC-MS in combination with multivariate statistical analyses including principal components analysis (PCA) and partial least squares-discriminant analysis (PLS-DA). Currently, the quality control of the NP-derived medicines is usually conducted using HPLC and is specified by one or two indicators. To create a superior quality control framework and avoid adulterated drugs, it is necessary to be able to determine and establish standards based on multiple ingredients using metabolic profiling and fingerprinting. Therefore, the application of various analytical tools in the quality control of NP-derived medicines forms the major part of this review. Veregen ® (Medigene AG, Planegg/Martinsried, Germany), which is the first botanical prescription drug approved by US Food and Drug Administration, is reviewed as an example that will hopefully provide future directions and perspectives on metabolomics technologies available for the quality control of NP-derived medicines.

Gut metabolome meets microbiome

DEFF Research Database (Denmark)

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

2018-01-01

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

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.

NMR-MPar: A Fault-Tolerance Approach for Multi-Core and Many-Core Processors

Directory of Open Access Journals (Sweden)

Vanessa Vargas

2018-03-01

Full Text Available Multi-core and many-core processors are a promising solution to achieve high performance by maintaining a lower power consumption. However, the degree of miniaturization makes them more sensitive to soft-errors. To improve the system reliability, this work proposes a fault-tolerance approach based on redundancy and partitioning principles called N-Modular Redundancy and M-Partitions (NMR-MPar. By combining both principles, this approach allows multi-/many-core processors to perform critical functions in mixed-criticality systems. Benefiting from the capabilities of these devices, NMR-MPar creates different partitions that perform independent functions. For critical functions, it is proposed that N partitions with the same configuration participate of an N-modular redundancy system. In order to validate the approach, a case study is implemented on the KALRAY Multi-Purpose Processing Array (MPPA-256 many-core processor running two parallel benchmark applications. The traveling salesman problem and matrix multiplication applications were selected to test different device’s resources. The effectiveness of NMR-MPar is assessed by software-implemented fault-injection. For evaluation purposes, it is considered that the system is intended to be used in avionics. Results show the improvement of the application reliability by two orders of magnitude when implementing NMR-MPar on the system. Finally, this work opens the possibility to use massive parallelism for dependable applications in embedded systems.

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

Science.gov (United States)

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

2014-01-01

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

Web-based resources for mass-spectrometry-based metabolomics: a user's guide.

Science.gov (United States)

Tohge, Takayuki; Fernie, Alisdair R

2009-03-01

In recent years, a plethora of web-based tools aimed at supporting mass-spectrometry-based metabolite profiling and metabolomics applications have appeared. Given the huge hurdles presented by the chemical diversity and dynamic range of the metabolites present in the plant kingdom, profiling the levels of a broad range of metabolites is highly challenging. Given the scale and costs involved in defining the plant metabolome, it is imperative that data are effectively shared between laboratories pursuing this goal. However, ensuring accurate comparison of samples run on the same machine within the same laboratory, let alone cross-machine and cross-laboratory comparisons, requires both careful experimentation and data interpretation. In this review, we present an overview of currently available software that aids either in peak identification or in the related field of peak alignment as well as those with utility in defining structural information of compounds and metabolic pathways.

Metabolomics to study functional consequences in peroxisomal disorders

NARCIS (Netherlands)

Herzog, K.

2017-01-01

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

Fragment-Linking Approach Using (19)F NMR Spectroscopy To Obtain Highly Potent and Selective Inhibitors of β-Secretase.

Science.gov (United States)

Jordan, John B; Whittington, Douglas A; Bartberger, Michael D; Sickmier, E Allen; Chen, Kui; Cheng, Yuan; Judd, Ted

2016-04-28

Fragment-based drug discovery (FBDD) has become a widely used tool in small-molecule drug discovery efforts. One of the most commonly used biophysical methods in detecting weak binding of fragments is nuclear magnetic resonance (NMR) spectroscopy. In particular, FBDD performed with (19)F NMR-based methods has been shown to provide several advantages over (1)H NMR using traditional magnetization-transfer and/or two-dimensional methods. Here, we demonstrate the utility and power of (19)F-based fragment screening by detailing the identification of a second-site fragment through (19)F NMR screening that binds to a specific pocket of the aspartic acid protease, β-secretase (BACE-1). The identification of this second-site fragment allowed the undertaking of a fragment-linking approach, which ultimately yielded a molecule exhibiting a more than 360-fold increase in potency while maintaining reasonable ligand efficiency and gaining much improved selectivity over cathepsin-D (CatD). X-ray crystallographic studies of the molecules demonstrated that the linked fragments exhibited binding modes consistent with those predicted from the targeted screening approach, through-space NMR data, and molecular modeling.

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

Directory of Open Access Journals (Sweden)

Hardy Nigel

2006-06-01

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

Exploratory metabolomics study of the experimental opisthorchiasis in a laboratory animal model (golden hamster, Mesocricetus auratus.

Directory of Open Access Journals (Sweden)

Daria A Kokova

2017-10-01

Full Text Available Opisthorchiasis is a parasitic infection caused by the liver flukes of the Opisthorchiidae family. Both experimental and epidemiological data strongly support a role of these parasites in the etiology of the hepatobiliary pathologies and an increased risk of intrahepatic cholangiocarcinoma. Understanding a functional link between the infection and hepatobiliary pathologies requires a detailed description a host-parasite interaction on different levels of biological regulation including the metabolic response on the infection. The last one, however, remains practically undocumented. Here we are describing a host response on Opisthorchiidae infection using a metabolomics approach and present the first exploratory metabolomics study of an experimental model of O. felineus infection.We conducted a Nuclear Magnetic Resonance (NMR based longitudinal metabolomics study involving a cohort of 30 animals with two degrees of infection and a control group. An exploratory analysis shows that the most noticeable trend (30% of total variance in the data was related to the gender differences. Therefore further analysis was done of each gender group separately applying a multivariate extension of the ANOVA-ASCA (ANOVA simultaneous component analysis. We show that in the males the infection specific time trends are present in the main component (43.5% variance, while in the females it is presented only in the second component and covers 24% of the variance. We have selected and annotated 24 metabolites associated with the observed effects and provided a physiological interpretation of the findings.The first exploratory metabolomics study an experimental model of O. felineus infection is presented. Our data show that at early stage of infection a response of an organism unfolds in a gender specific manner. Also main physiological mechanisms affected appear rather nonspecific (a status of the metabolic stress the data provides a set of the hypothesis for a search

Establishment of quantitative severity evaluation model for spinal cord injury by metabolomic fingerprinting.

Directory of Open Access Journals (Sweden)

Jin Peng

Full Text Available Spinal cord injury (SCI is a devastating event with a limited hope for recovery and represents an enormous public health issue. It is crucial to understand the disturbances in the metabolic network after SCI to identify injury mechanisms and opportunities for treatment intervention. Through plasma 1H-nuclear magnetic resonance (NMR screening, we identified 15 metabolites that made up an "Eigen-metabolome" capable of distinguishing rats with severe SCI from healthy control rats. Forty enzymes regulated these 15 metabolites in the metabolic network. We also found that 16 metabolites regulated by 130 enzymes in the metabolic network impacted neurobehavioral recovery. Using the Eigen-metabolome, we established a linear discrimination model to cluster rats with severe and mild SCI and control rats into separate groups and identify the interactive relationships between metabolic biomarkers in the global metabolic network. We identified 10 clusters in the global metabolic network and defined them as distinct metabolic disturbance domains of SCI. Metabolic paths such as retinal, glycerophospholipid, arachidonic acid metabolism; NAD-NADPH conversion process, tyrosine metabolism, and cadaverine and putrescine metabolism were included. In summary, we presented a novel interdisciplinary method that integrates metabolomics and global metabolic network analysis to visualize metabolic network disturbances after SCI. Our study demonstrated the systems biological study paradigm that integration of 1H-NMR, metabolomics, and global metabolic network analysis is useful to visualize complex metabolic disturbances after severe SCI. Furthermore, our findings may provide a new quantitative injury severity evaluation model for clinical use.

Application of Metabolomics to Study Effects of Bariatric Surgery

Directory of Open Access Journals (Sweden)

Paulina Samczuk

2018-01-01

Full Text Available Bariatric surgery was born in the 1950s at the University of Minnesota. From this time, it continues to evolve and, by the same token, gives new or better possibilities to treat not only obesity but also associated comorbidities. Metabolomics is also a relatively young science discipline, and similarly, it shows great potential for the comprehensive study of the dynamic alterations of the metabolome. It has been widely used in medicine, biology studies, biomarker discovery, and prognostic evaluations. Currently, several dozen metabolomics studies were performed to study the effects of bariatric surgery. LC-MS and NMR are the most frequently used techniques to study main effects of RYGB or SG. Research has yield many interesting results involving not only clinical parameters but also molecular modulations. Detected changes pertain to amino acid, lipids, carbohydrates, or gut microbiota alterations. It proves that including bariatric surgery to metabolic surgery is warranted. However, many molecular modulations after those procedures remain unexplained. Therefore, application of metabolomics to study this field seems to be a proper solution. New findings can suggest new directions of surgery technics modifications, contribute to broadening knowledge about obesity and diseases related to it, and perhaps develop nonsurgical methods of treatment in the future.

Impact of red meat consumption on the metabolome of rats.

Science.gov (United States)

Jakobsen, Louise M A; Yde, Christian C; Van Hecke, Thomas; Jessen, Randi; Young, Jette F; De Smet, Stefaan; Bertram, Hanne Christine

2017-03-01

The scope of the present study was to investigate the effects of red versus white meat intake on the metabolome of rats. Twenty-four male Sprague-Dawley rats were randomly assigned to 15 days of ad libitum feeding of one of four experimental diets: (i) lean chicken, (ii) chicken with lard, (iii) lean beef, and (iv) beef with lard. Urine, feces, plasma, and colon tissue samples were analyzed using 1 H NMR-based metabolomics and real-time PCR was performed on colon tissue to examine the expression of specific genes. Urinary excretion of acetate and anserine was higher after chicken intake, while carnosine, fumarate, and trimethylamine N-oxide excretion were higher after beef intake. In colon tissue, higher choline levels and lower lipid levels were found after intake of chicken compared to beef. Expression of the apc gene was higher in response to the lean chicken and beef with lard diets. Correlation analysis revealed that intestinal apc gene expression was correlated with fecal lactate content (R 2 = 0.65). This study is the first to identify specific differences in the metabolome related to the intake of red and white meat. These differences may reflect perturbations in endogenous metabolism that can be linked to the proposed harmful effects associated with intake of red meat. © 2016 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

Science.gov (United States)

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

2016-02-01

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

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

International Nuclear Information System (INIS)

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

2010-01-01

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

The effects of liraglutide in mice with diet-induced obesity studied by metabolomics

Czech Academy of Sciences Publication Activity Database

Bugáňová, M.; Pelantová, H.; Holubová, M.; Šedivá, B.; Maletínská, L.; Železná, B.; Kuneš, Jaroslav; Kačer, P.; Kuzma, M.; Haluzík, M.

2017-01-01

Roč. 233, č. 1 (2017), s. 93-104 ISSN 0022-0795 Institutional support: RVO:67985823 Keywords : NMR metabolomics * obesity type 2 * diabetes mellitus * liraglutide * mouse urine Subject RIV: FB - Endocrinology, Diabetology, Metabolism, Nutrition OBOR OECD: Endocrinology and metabolism (including diabetes , hormones) Impact factor: 4.706, year: 2016

1H-NMR, 1H-NMR T2-edited, and 2D-NMR in bipolar disorder metabolic profiling.

Science.gov (United States)

Sethi, Sumit; Pedrini, Mariana; Rizzo, Lucas B; Zeni-Graiff, Maiara; Mas, Caroline Dal; Cassinelli, Ana Cláudia; Noto, Mariane N; Asevedo, Elson; Cordeiro, Quirino; Pontes, João G M; Brasil, Antonio J M; Lacerda, Acioly; Hayashi, Mirian A F; Poppi, Ronei; Tasic, Ljubica; Brietzke, Elisa

2017-12-01

The objective of this study was to identify molecular alterations in the human blood serum related to bipolar disorder, using nuclear magnetic resonance (NMR) spectroscopy and chemometrics. Metabolomic profiling, employing 1 H-NMR, 1 H-NMR T 2 -edited, and 2D-NMR spectroscopy and chemometrics of human blood serum samples from patients with bipolar disorder (n = 26) compared with healthy volunteers (n = 50) was performed. The investigated groups presented distinct metabolic profiles, in which the main differential metabolites found in the serum sample of bipolar disorder patients compared with those from controls were lipids, lipid metabolism-related molecules (choline, myo-inositol), and some amino acids (N-acetyl-L-phenyl alanine, N-acetyl-L-aspartyl-L-glutamic acid, L-glutamine). In addition, amygdalin, α-ketoglutaric acid, and lipoamide, among other compounds, were also present or were significantly altered in the serum of bipolar disorder patients. The data presented herein suggest that some of these metabolites differentially distributed between the groups studied may be directly related to the bipolar disorder pathophysiology. The strategy employed here showed significant potential for exploring pathophysiological features and molecular pathways involved in bipolar disorder. Thus, our findings may contribute to pave the way for future studies aiming at identifying important potential biomarkers for bipolar disorder diagnosis or progression follow-up.

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

Directory of Open Access Journals (Sweden)

Ana Rita Lima

2016-08-01

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

The Role of Mass Spectrometry-Based Metabolomics in Medical Countermeasures Against Radiation

Science.gov (United States)

Patterson, Andrew D.; Lanz, Christian; Gonzalez, Frank J.; Idle, Jeffrey R.

2013-01-01

Radiation metabolomics can be defined as the global profiling of biological fluids to uncover latent, endogenous small molecules whose concentrations change in a dose-response manner following exposure to ionizing radiation. In response to the potential threat of nuclear or radiological terrorism, the Center for High-Throughput Minimally Invasive Radiation Biodosimetry (CMCR) was established to develop field-deployable biodosimeters based, in principle, on rapid analysis by mass spectrometry of readily and easily obtainable biofluids. In this review, we briefly summarize radiation biology and key events related to actual and potential nuclear disasters, discuss the important contributions the field of mass spectrometry has made to the field of radiation metabolomics, and summarize current discovery efforts to use mass spectrometry-based metabolomics to identify dose-responsive urinary constituents, and ultimately to build and deploy a noninvasive high-throughput biodosimeter. PMID:19890938

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

Reducing acquisition times in multidimensional NMR with a time-optimized Fourier encoding algorithm

Energy Technology Data Exchange (ETDEWEB)

Zhang, Zhiyong [Department of Chemical Physics, Weizmann Institute of Science, Rehovot 76100 (Israel); Department of Electronic Science, Fujian Provincial Key Laboratory of Plasma and Magnetic Resonance, Xiamen University, Xiamen, Fujian 361005 (China); Smith, Pieter E. S.; Frydman, Lucio, E-mail: lucio.frydman@weizmann.ac.il [Department of Chemical Physics, Weizmann Institute of Science, Rehovot 76100 (Israel)

2014-11-21

Speeding up the acquisition of multidimensional nuclear magnetic resonance (NMR) spectra is an important topic in contemporary NMR, with central roles in high-throughput investigations and analyses of marginally stable samples. A variety of fast NMR techniques have been developed, including methods based on non-uniform sampling and Hadamard encoding, that overcome the long sampling times inherent to schemes based on fast-Fourier-transform (FFT) methods. Here, we explore the potential of an alternative fast acquisition method that leverages a priori knowledge, to tailor polychromatic pulses and customized time delays for an efficient Fourier encoding of the indirect domain of an NMR experiment. By porting the encoding of the indirect-domain to the excitation process, this strategy avoids potential artifacts associated with non-uniform sampling schemes and uses a minimum number of scans equal to the number of resonances present in the indirect dimension. An added convenience is afforded by the fact that a usual 2D FFT can be used to process the generated data. Acquisitions of 2D heteronuclear correlation NMR spectra on quinine and on the anti-inflammatory drug isobutyl propionic phenolic acid illustrate the new method's performance. This method can be readily automated to deal with complex samples such as those occurring in metabolomics, in in-cell as well as in in vivo NMR applications, where speed and temporal stability are often primary concerns.

Reducing acquisition times in multidimensional NMR with a time-optimized Fourier encoding algorithm

International Nuclear Information System (INIS)

Zhang, Zhiyong; Smith, Pieter E. S.; Frydman, Lucio

2014-01-01

Speeding up the acquisition of multidimensional nuclear magnetic resonance (NMR) spectra is an important topic in contemporary NMR, with central roles in high-throughput investigations and analyses of marginally stable samples. A variety of fast NMR techniques have been developed, including methods based on non-uniform sampling and Hadamard encoding, that overcome the long sampling times inherent to schemes based on fast-Fourier-transform (FFT) methods. Here, we explore the potential of an alternative fast acquisition method that leverages a priori knowledge, to tailor polychromatic pulses and customized time delays for an efficient Fourier encoding of the indirect domain of an NMR experiment. By porting the encoding of the indirect-domain to the excitation process, this strategy avoids potential artifacts associated with non-uniform sampling schemes and uses a minimum number of scans equal to the number of resonances present in the indirect dimension. An added convenience is afforded by the fact that a usual 2D FFT can be used to process the generated data. Acquisitions of 2D heteronuclear correlation NMR spectra on quinine and on the anti-inflammatory drug isobutyl propionic phenolic acid illustrate the new method's performance. This method can be readily automated to deal with complex samples such as those occurring in metabolomics, in in-cell as well as in in vivo NMR applications, where speed and temporal stability are often primary concerns

Metabolomics through the lens of precision cardiovascular medicine.

Science.gov (United States)

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

2017-03-20

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

Towards a Universal Approach Based on Omics Technologies for the Quality Control of Food.

Science.gov (United States)

Ferri, Emanuele; Galimberti, Andrea; Casiraghi, Maurizio; Airoldi, Cristina; Ciaramelli, Carlotta; Palmioli, Alessandro; Mezzasalma, Valerio; Bruni, Ilaria; Labra, Massimo

2015-01-01

In the last decades, food science has greatly developed, turning from the consideration of food as mere source of energy to a growing awareness on its importance for health and particularly in reducing the risk of diseases. Such vision led to an increasing attention towards the origin and quality of raw materials as well as their derived food products. The continuous advance in molecular biology allowed setting up efficient and universal omics tools to unequivocally identify the origin of food items and their traceability. In this review, we considered the application of a genomics approach known as DNA barcoding in characterizing the composition of foodstuffs and its traceability along the food supply chain. Moreover, metabolomics analytical strategies based on Nuclear Magnetic Resonance (NMR) and Mass Spectroscopy (MS) were discussed as they also work well in evaluating food quality. The combination of both approaches allows us to define a sort of molecular labelling of food that is easily understandable by the operators involved in the food sector: producers, distributors, and consumers. Current technologies based on digital information systems such as web platforms and smartphone apps can facilitate the adoption of such molecular labelling.

Towards a Universal Approach Based on Omics Technologies for the Quality Control of Food

Directory of Open Access Journals (Sweden)

Emanuele Ferri

2015-01-01

Full Text Available In the last decades, food science has greatly developed, turning from the consideration of food as mere source of energy to a growing awareness on its importance for health and particularly in reducing the risk of diseases. Such vision led to an increasing attention towards the origin and quality of raw materials as well as their derived food products. The continuous advance in molecular biology allowed setting up efficient and universal omics tools to unequivocally identify the origin of food items and their traceability. In this review, we considered the application of a genomics approach known as DNA barcoding in characterizing the composition of foodstuffs and its traceability along the food supply chain. Moreover, metabolomics analytical strategies based on Nuclear Magnetic Resonance (NMR and Mass Spectroscopy (MS were discussed as they also work well in evaluating food quality. The combination of both approaches allows us to define a sort of molecular labelling of food that is easily understandable by the operators involved in the food sector: producers, distributors, and consumers. Current technologies based on digital information systems such as web platforms and smartphone apps can facilitate the adoption of such molecular labelling.

Towards a Universal Approach Based on Omics Technologies for the Quality Control of Food

Science.gov (United States)

Ferri, Emanuele; Airoldi, Cristina; Ciaramelli, Carlotta; Palmioli, Alessandro; Bruni, Ilaria

2015-01-01

In the last decades, food science has greatly developed, turning from the consideration of food as mere source of energy to a growing awareness on its importance for health and particularly in reducing the risk of diseases. Such vision led to an increasing attention towards the origin and quality of raw materials as well as their derived food products. The continuous advance in molecular biology allowed setting up efficient and universal omics tools to unequivocally identify the origin of food items and their traceability. In this review, we considered the application of a genomics approach known as DNA barcoding in characterizing the composition of foodstuffs and its traceability along the food supply chain. Moreover, metabolomics analytical strategies based on Nuclear Magnetic Resonance (NMR) and Mass Spectroscopy (MS) were discussed as they also work well in evaluating food quality. The combination of both approaches allows us to define a sort of molecular labelling of food that is easily understandable by the operators involved in the food sector: producers, distributors, and consumers. Current technologies based on digital information systems such as web platforms and smartphone apps can facilitate the adoption of such molecular labelling. PMID:26783518

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

Science.gov (United States)

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

2015-04-29

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

Getting Your Peaks in Line: A Review of Alignment Methods for NMR Spectral Data

Directory of Open Access Journals (Sweden)

Trung Nghia Vu

2013-04-01

Full Text Available One of the most significant challenges in the comparative analysis of Nuclear Magnetic Resonance (NMR metabolome profiles is the occurrence of shifts between peaks across different spectra, for example caused by fluctuations in pH, temperature, instrument factors and ion content. Proper alignment of spectral peaks is therefore often a crucial preprocessing step prior to downstream quantitative analysis. Various alignment methods have been developed specifically for this purpose. Other methods were originally developed to align other data types (GC, LC, SELDI-MS, etc., but can also be applied to NMR data. This review discusses the available methods, as well as related problems such as reference determination or the evaluation of alignment quality. We present a generic alignment framework that allows for comparison and classification of different alignment approaches according to their algorithmic principles, and we discuss their performance.

Metabolic profiling of human lung cancer blood plasma using 1H NMR spectroscopy

Science.gov (United States)

Kokova, Daria; Dementeva, Natalia; Kotelnikov, Oleg; Ponomaryova, Anastasia; Cherdyntseva, Nadezhda; Kzhyshkowska, Juliya

2017-11-01

Lung cancer (both small cell and non-small cell) is the second most common cancer in both men and women. The article represents results of evaluating of the plasma metabolic profiles of 100 lung cancer patients and 100 controls to investigate significant metabolites using 400 MHz 1H NMR spectrometer. The results of multivariate statistical analysis show that a medium-field NMR spectrometer can obtain the data which are already sufficient for clinical metabolomics.

Metabolomics: beyond biomarkers and towards mechanisms

Science.gov (United States)

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

2017-01-01

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

Probing water motion in heterogenous systems : a multi-parameter NMR approach

NARCIS (Netherlands)

Dusschoten, van D.

1996-01-01

In this Thesis a practical approach is presented to study water mobility in heterogeneous systems by a number of novel NMR sequences. The major part of this Thesis describes how the reliability of diffusion measurements can be improved using some of the novel NMR sequences. The

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.

Role of metabolomics in TBI research

Science.gov (United States)

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

2016-01-01

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

LipSpin: A New Bioinformatics Tool for Quantitative 1H NMR Lipid Profiling.

Science.gov (United States)

Barrilero, Rubén; Gil, Miriam; Amigó, Núria; Dias, Cintia B; Wood, Lisa G; Garg, Manohar L; Ribalta, Josep; Heras, Mercedes; Vinaixa, Maria; Correig, Xavier

2018-02-06

The structural similarity among lipid species and the low sensitivity and spectral resolution of nuclear magnetic resonance (NMR) have traditionally hampered the routine use of 1 H NMR lipid profiling of complex biological samples in metabolomics, which remains mostly manual and lacks freely available bioinformatics tools. However, 1 H NMR lipid profiling provides fast quantitative screening of major lipid classes (fatty acids, glycerolipids, phospholipids, and sterols) and some individual species and has been used in several clinical and nutritional studies, leading to improved risk prediction models. In this Article, we present LipSpin, a free and open-source bioinformatics tool for quantitative 1 H NMR lipid profiling. LipSpin implements a constrained line shape fitting algorithm based on voigt profiles and spectral templates from spectra of lipid standards, which automates the analysis of severely overlapped spectral regions and lipid signals with complex coupling patterns. LipSpin provides the most detailed quantification of fatty acid families and choline phospholipids in serum lipid samples by 1 H NMR to date. Moreover, analytical and clinical results using LipSpin quantifications conform with other techniques commonly used for lipid analysis.

Ameliorating effects of Mango (Mangifera indica L.) fruit on plasma ethanol level in a mouse model assessed with 1H-NMR based metabolic profiling

Science.gov (United States)

Kim, So-Hyun; K. Cho, Somi; Min, Tae-Sun; Kim, Yujin; Yang, Seung-Ok; Kim, Hee-Su; Hyun, Sun-Hee; Kim, Hana; Kim, Young-Suk; Choi, Hyung-Kyoon

2011-01-01

The ameliorating effects of Mango (Mangifera indica L.) flesh and peel samples on plasma ethanol level were investigated using a mouse model. Mango fruit samples remarkably decreased mouse plasma ethanol levels and increased the activities of alcohol dehydrogenase and acetaldehyde dehydrogenase. The 1H-NMR-based metabolomic technique was employed to investigate the differences in metabolic profiles of mango fruits, and mouse plasma samples fed with mango fruit samples. The partial least squares-discriminate analysis of 1H-NMR spectral data of mouse plasma demonstrated that there were clear separations among plasma samples from mice fed with buffer, mango flesh and peel. A loading plot demonstrated that metabolites from mango fruit, such as fructose and aspartate, might stimulate alcohol degradation enzymes. This study suggests that mango flesh and peel could be used as resources for functional foods intended to decrease plasma ethanol level after ethanol uptake. PMID:21562641

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

Directory of Open Access Journals (Sweden)

Luka Andrisic

2018-04-01

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

Metabolomics as a tool in the identification of dietary biomarkers.

Science.gov (United States)

Gibbons, Helena; Brennan, Lorraine

2017-02-01

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

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.

A phytochemical comparison of saw palmetto products using gas chromatography and 1H nuclear magnetic resonance spectroscopy metabolomic profiling

Science.gov (United States)

Booker, Anthony; Suter, Andy; Krnjic, Ana; Strassel, Brigitte; Zloh, Mire; Said, Mazlina; Heinrich, Michael

2014-01-01

Objectives Preparations containing saw palmetto berries are used in the treatment of benign prostatic hyperplasia (BPH). There are many products on the market, and relatively little is known about their chemical variability and specifically the composition and quality of different saw palmetto products notwithstanding that in 2000, an international consultation paper from the major urological associations from the five continents on treatments for BPH demanded further research on this topic. Here, we compare two analytical approaches and characterise 57 different saw palmetto products. Methods An established method – gas chromatography – was used for the quantification of nine fatty acids, while a novel approach of metabolomic profiling using 1H nuclear magnetic resonance (NMR) spectroscopy was used as a fingerprinting tool to assess the overall composition of the extracts. Key findings The phytochemical analysis determining the fatty acids showed a high level of heterogeneity of the different products in the total amount and of nine single fatty acids. A robust and reproducible 1H NMR spectroscopy method was established, and the results showed that it was possible to statistically differentiate between saw palmetto products that had been extracted under different conditions but not between products that used a similar extraction method. Principal component analysis was able to determine those products that had significantly different metabolites. Conclusions The metabolomic approach developed offers novel opportunities for quality control along the value chain of saw palmetto and needs to be followed further, as with this method, the complexity of a herbal extract can be better assessed than with the analysis of a single group of constituents. PMID:24417505

A phytochemical comparison of saw palmetto products using gas chromatography and (1) H nuclear magnetic resonance spectroscopy metabolomic profiling.

Science.gov (United States)

Booker, Anthony; Suter, Andy; Krnjic, Ana; Strassel, Brigitte; Zloh, Mire; Said, Mazlina; Heinrich, Michael

2014-06-01

Preparations containing saw palmetto berries are used in the treatment of benign prostatic hyperplasia (BPH). There are many products on the market, and relatively little is known about their chemical variability and specifically the composition and quality of different saw palmetto products notwithstanding that in 2000, an international consultation paper from the major urological associations from the five continents on treatments for BPH demanded further research on this topic. Here, we compare two analytical approaches and characterise 57 different saw palmetto products. An established method - gas chromatography - was used for the quantification of nine fatty acids, while a novel approach of metabolomic profiling using (1) H nuclear magnetic resonance (NMR) spectroscopy was used as a fingerprinting tool to assess the overall composition of the extracts. The phytochemical analysis determining the fatty acids showed a high level of heterogeneity of the different products in the total amount and of nine single fatty acids. A robust and reproducible (1) H NMR spectroscopy method was established, and the results showed that it was possible to statistically differentiate between saw palmetto products that had been extracted under different conditions but not between products that used a similar extraction method. Principal component analysis was able to determine those products that had significantly different metabolites. The metabolomic approach developed offers novel opportunities for quality control along the value chain of saw palmetto and needs to be followed further, as with this method, the complexity of a herbal extract can be better assessed than with the analysis of a single group of constituents. © 2014 The Authors. Journal of Pharmacy and Pharmacology published by John Wiley & Sons Ltd on behalf of Royal Pharmaceutical Society.

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.

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

Stripline-based microfluidic devices for high-resolution NMR spectroscopy

NARCIS (Netherlands)

Bart, J.

2009-01-01

A novel route towards microchip integrated NMR analysis was studied. For NMR analysis of mass-limited samples, research has focussed for decennia on microsolenoidal or planar helical detection coils on microfluidic substrates. Since these approaches suffer from static field distortion resulting in

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

Metabolic responses of Eisenia fetida after sub-lethal exposure to organic contaminants with different toxic modes of action

Energy Technology Data Exchange (ETDEWEB)

McKelvie, Jennifer R.; Wolfe, David M.; Celejewski, Magda A. [Department of Physical and Environmental Sciences, University of Toronto, 1265 Military Trail Toronto, ON M1C 1A4 (Canada); Alaee, Mehran [Environment Canada, 867 Lakeshore Rd., P.O. Box 5050, Burlington, ON L7R 4A6 (Canada); Simpson, Andre J. [Department of Physical and Environmental Sciences, University of Toronto, 1265 Military Trail Toronto, ON M1C 1A4 (Canada); Simpson, Myrna J., E-mail: myrna.simpson@utoronto.ca [Department of Physical and Environmental Sciences, University of Toronto, 1265 Military Trail Toronto, ON M1C 1A4 (Canada)

2011-12-15

Nuclear magnetic resonance (NMR) - based metabolomics has the potential to identify toxic responses of contaminants within a mixture in contaminated soil. This study evaluated the metabolic response of Eisenia fetida after exposure to an array of organic compounds to determine whether contaminant-specific responses could be identified. The compounds investigated in contact tests included: two pesticides (carbaryl and chlorpyrifos), three pharmaceuticals (carbamazephine, estrone and caffeine), two persistent organohalogens (Aroclor 1254 and PBDE 209) and two industrial compounds (nonylphenol and dimethyl phthalate). Control and contaminant-exposed metabolic profiles were distinguished using principal component analysis and potential contaminant-specific biomarkers of exposure were found for several contaminants. These results suggest that NMR-based metabolomics offers considerable promise for differentiating between the different toxic modes of action (MOA) associated with sub-lethal toxicity to earthworms. - Highlights: > NMR-based earthworm metabolomic analysis of the toxic mode of action of various environmental contaminants. > Organic chemicals with different toxic modes of action resulted in varied metabolomic responses for E. fetida. > NMR-based metabolomics differentiates between the different modes of action associated with sub-lethal toxicity. - {sup 1}H NMR metabolomics was used to identify potential biomarkers of organic contaminant exposure in Eisenia fetida earthworms.

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.

Metabolomics approach for discovering disease biomarkers and understanding metabolic pathway

Directory of Open Access Journals (Sweden)

Jeeyoun Jung

2011-12-01

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

Metabolomics in Population-Based Research

Science.gov (United States)

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

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.

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

PAMDB: a comprehensive Pseudomonas aeruginosa metabolome database.

Science.gov (United States)

Huang, Weiliang; Brewer, Luke K; Jones, Jace W; Nguyen, Angela T; Marcu, Ana; Wishart, David S; Oglesby-Sherrouse, Amanda G; Kane, Maureen A; Wilks, Angela

2018-01-04

The Pseudomonas aeruginosaMetabolome Database (PAMDB, http://pseudomonas.umaryland.edu) is a searchable, richly annotated metabolite database specific to P. aeruginosa. P. aeruginosa is a soil organism and significant opportunistic pathogen that adapts to its environment through a versatile energy metabolism network. Furthermore, P. aeruginosa is a model organism for the study of biofilm formation, quorum sensing, and bioremediation processes, each of which are dependent on unique pathways and metabolites. The PAMDB is modelled on the Escherichia coli (ECMDB), yeast (YMDB) and human (HMDB) metabolome databases and contains >4370 metabolites and 938 pathways with links to over 1260 genes and proteins. The database information was compiled from electronic databases, journal articles and mass spectrometry (MS) metabolomic data obtained in our laboratories. For each metabolite entered, we provide detailed compound descriptions, names and synonyms, structural and physiochemical information, nuclear magnetic resonance (NMR) and MS spectra, enzymes and pathway information, as well as gene and protein sequences. The database allows extensive searching via chemical names, structure and molecular weight, together with gene, protein and pathway relationships. The PAMBD and its future iterations will provide a valuable resource to biologists, natural product chemists and clinicians in identifying active compounds, potential biomarkers and clinical diagnostics. © The Author(s) 2017. Published by Oxford University Press on behalf of Nucleic Acids Research.

Energetics of endurance exercise in young horses determined by nuclear magnetic resonance metabolomics

Directory of Open Access Journals (Sweden)

Margaux Marie-Hélène, Olivia Luck

2015-07-01

Full Text Available Long-term endurance exercise severely affects metabolism in both human and animal athletes resulting in serious risk of metabolic disorders during or after competition. Young horses (up to 6 years old can compete in races up to 90 km despite limited scientific knowledge of energetic metabolism responses to long distance exercise in these animals. The hypothesis of this study was that there would be a strong effect of endurance exercise on the metabolomic profiles of young horses and that the energetic metabolism response in young horses would be different from that of more experienced horses. Metabolomic profiling is a powerful method that combines Nuclear magnetic resonance (NMR spectrometry with supervised orthogonal projection on latent structure (OPLS statistical analysis. 1H-NMR spectra were obtained from plasma samples drawn from young horses (before and after competition. The spectra obtained before and after the race from the same horse (92 samples were compared using OPLS. The statistical parameters showed the robustness of the model (R2Y=0.947, Q2Y=0.856 and CV-ANOVA p-value < 0.001. For confirmation of the predictive value of the model, a test set of 104 sample spectra were projected by the model, which provided perfect predictions as the area under the receiving-operator curve was 1. The metabolomic profile determined with the OPLS model showed that glycemia after the race was lower than glycemia before the race, despite the involvement of lipid and protein catabolism. An OPLS model was calculated to compare spectra obtained on plasma taken after the race from 6-year-old horses and from experienced horses (cross-validated ANOVA p-value < 0.001. The comparison of metabolomic profiles in young horses to those from experienced horses showed that experienced horses maintained their glycemia with higher levels of lactate and a decrease of plasma lipids after the race.

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

DEFF Research Database (Denmark)

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

2017-01-01

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

MetaFIND: A feature analysis tool for metabolomics data

Directory of Open Access Journals (Sweden)

Cunningham Pádraig

2008-11-01

Full Text Available Abstract Background Metabolomics, or metabonomics, refers to the quantitative analysis of all metabolites present within a biological sample and is generally carried out using NMR spectroscopy or Mass Spectrometry. Such analysis produces a set of peaks, or features, indicative of the metabolic composition of the sample and may be used as a basis for sample classification. Feature selection may be employed to improve classification accuracy or aid model explanation by establishing a subset of class discriminating features. Factors such as experimental noise, choice of technique and threshold selection may adversely affect the set of selected features retrieved. Furthermore, the high dimensionality and multi-collinearity inherent within metabolomics data may exacerbate discrepancies between the set of features retrieved and those required to provide a complete explanation of metabolite signatures. Given these issues, the latter in particular, we present the MetaFIND application for 'post-feature selection' correlation analysis of metabolomics data. Results In our evaluation we show how MetaFIND may be used to elucidate metabolite signatures from the set of features selected by diverse techniques over two metabolomics datasets. Importantly, we also show how MetaFIND may augment standard feature selection and aid the discovery of additional significant features, including those which represent novel class discriminating metabolites. MetaFIND also supports the discovery of higher level metabolite correlations. Conclusion Standard feature selection techniques may fail to capture the full set of relevant features in the case of high dimensional, multi-collinear metabolomics data. We show that the MetaFIND 'post-feature selection' analysis tool may aid metabolite signature elucidation, feature discovery and inference of metabolic correlations.

The future of metabolomics in ELIXIR

Science.gov (United States)

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

2017-01-01

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

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.

The combination of four analytical methods to explore skeletal muscle metabolomics: Better coverage of metabolic pathways or a marketing argument?

Science.gov (United States)

Bruno, C; Patin, F; Bocca, C; Nadal-Desbarats, L; Bonnier, F; Reynier, P; Emond, P; Vourc'h, P; Joseph-Delafont, K; Corcia, P; Andres, C R; Blasco, H

2018-01-30

Metabolomics is an emerging science based on diverse high throughput methods that are rapidly evolving to improve metabolic coverage of biological fluids and tissues. Technical progress has led researchers to combine several analytical methods without reporting the impact on metabolic coverage of such a strategy. The objective of our study was to develop and validate several analytical techniques (mass spectrometry coupled to gas or liquid chromatography and nuclear magnetic resonance) for the metabolomic analysis of small muscle samples and evaluate the impact of combining methods for more exhaustive metabolite covering. We evaluated the muscle metabolome from the same pool of mouse muscle samples after 2 metabolite extraction protocols. Four analytical methods were used: targeted flow injection analysis coupled with mass spectrometry (FIA-MS/MS), gas chromatography coupled with mass spectrometry (GC-MS), liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS), and nuclear magnetic resonance (NMR) analysis. We evaluated the global variability of each compound i.e., analytical (from quality controls) and extraction variability (from muscle extracts). We determined the best extraction method and we reported the common and distinct metabolites identified based on the number and identity of the compounds detected with low analytical variability (variation coefficient<30%) for each method. Finally, we assessed the coverage of muscle metabolic pathways obtained. Methanol/chloroform/water and water/methanol were the best extraction solvent for muscle metabolome analysis by NMR and MS, respectively. We identified 38 metabolites by nuclear magnetic resonance, 37 by FIA-MS/MS, 18 by GC-MS, and 80 by LC-HRMS. The combination led us to identify a total of 132 metabolites with low variability partitioned into 58 metabolic pathways, such as amino acid, nitrogen, purine, and pyrimidine metabolism, and the citric acid cycle. This combination also showed

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

Science.gov (United States)

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

2016-10-01

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

Applications of solid-state Nuclear Magnetic Resonance (NMR) in studies of Portland cements-based materials

DEFF Research Database (Denmark)

Skibsted, Jørgen; Andersen, Morten Daugaard; Jakobsen, Hans Jørgen

2007-01-01

Solid-state NMR spectroscopy represents an important research tool in the characterization of a range of structural properties for cement-based materials. Different approaches of the technique can be used to obtain information on hydration kinetics, mobile and bound water, porosity, and local...... atomic structures. After a short introduction to these NMR techniques, it is exemplified how magic-angle spinning (MAS) NMR can provide quantitative and structural information about specific phases in anhydrous and hydrated Portland cements with main emphasis on the incorporation of Al3+ ions...

The effects of liraglutide in mice with diet-induced obesity studied by metabolomics

Czech Academy of Sciences Publication Activity Database

Bugáňová, Martina; Pelantová, Helena; Holubová, Martina; Šedivá, B.; Maletínská, Lenka; Železná, Blanka; Kuneš, Jaroslav; Kačer, Petr; Kuzma, Marek; Haluzík, M.

2017-01-01

Roč. 233, č. 1 (2017), s. 93-104 ISSN 0022-0795 R&D Projects: GA ČR GA13-14105S; GA MŠk(CZ) LO1509 Institutional support: RVO:61388971 ; RVO:61388963 Keywords : NMR metabolomics * obesity * type 2 diabetes mellitus Subject RIV: EE - Microbiology, Virology OBOR OECD: Microbiology; Physiology (including cytology) (UOCHB-X) Impact factor: 4.706, year: 2016

Evaluation of Normalization Methods to Pave the Way Towards Large-Scale LC-MS-Based Metabolomics Profiling Experiments

Science.gov (United States)

Valkenborg, Dirk; Baggerman, Geert; Vanaerschot, Manu; Witters, Erwin; Dujardin, Jean-Claude; Burzykowski, Tomasz; Berg, Maya

2013-01-01

Abstract Combining liquid chromatography-mass spectrometry (LC-MS)-based metabolomics experiments that were collected over a long period of time remains problematic due to systematic variability between LC-MS measurements. Until now, most normalization methods for LC-MS data are model-driven, based on internal standards or intermediate quality control runs, where an external model is extrapolated to the dataset of interest. In the first part of this article, we evaluate several existing data-driven normalization approaches on LC-MS metabolomics experiments, which do not require the use of internal standards. According to variability measures, each normalization method performs relatively well, showing that the use of any normalization method will greatly improve data-analysis originating from multiple experimental runs. In the second part, we apply cyclic-Loess normalization to a Leishmania sample. This normalization method allows the removal of systematic variability between two measurement blocks over time and maintains the differential metabolites. In conclusion, normalization allows for pooling datasets from different measurement blocks over time and increases the statistical power of the analysis, hence paving the way to increase the scale of LC-MS metabolomics experiments. From our investigation, we recommend data-driven normalization methods over model-driven normalization methods, if only a few internal standards were used. Moreover, data-driven normalization methods are the best option to normalize datasets from untargeted LC-MS experiments. PMID:23808607

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

Directory of Open Access Journals (Sweden)

Panagiotis Arapitsas

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

A Metabolomic Approach to the Study of Wine Micro-Oxygenation

Science.gov (United States)

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

2012-01-01

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

Metabolic profiling of goldfish (Carassius auratis) after long-term glyphosate-based herbicide exposure.

Science.gov (United States)

Li, Ming-Hui; Ruan, Ling-Yu; Zhou, Jin-Wei; Fu, Yong-Hong; Jiang, Lei; Zhao, He; Wang, Jun-Song

2017-07-01

Glyphosate is an efficient herbicide widely used worldwide. However, its toxicity to non-targeted organisms has not been fully elucidated. In this study, the toxicity of glyphosate-based herbicide was evaluated on goldfish (Carassius auratus) after long-term exposure. Tissues of brains, kidneys and livers were collected and submitted to NMR-based metabolomics analysis and histopathological inspection. Plasma was collected and the blood biochemical indexes of AST, ALT, BUN, CRE, LDH, SOD, GSH-Px, GR and MDA were measured. Long-term glyphosate exposure caused disorders of blood biochemical indexes and renal tissue injury in goldfish. Metabolomics analysis combined with correlation network analysis uncovered significant perturbations in oxidative stress, energy metabolism, amino acids metabolism and nucleosides metabolism in glyphosate dosed fish, which provide new clues to the toxicity of glyphosate. This integrated metabolomics approach showed its applicability in discovering the toxic mechanisms of pesticides, which provided new strategy for the assessment of the environmental risk of herbicides to non-target organisms. Copyright © 2017 Elsevier B.V. All rights reserved.

The food metabolome: a window over dietary exposure.

Science.gov (United States)

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

2014-06-01

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

Metabolic responses of Eisenia fetida after sub-lethal exposure to organic contaminants with different toxic modes of action

International Nuclear Information System (INIS)

McKelvie, Jennifer R.; Wolfe, David M.; Celejewski, Magda A.; Alaee, Mehran; Simpson, Andre J.; Simpson, Myrna J.

2011-01-01

Nuclear magnetic resonance (NMR) - based metabolomics has the potential to identify toxic responses of contaminants within a mixture in contaminated soil. This study evaluated the metabolic response of Eisenia fetida after exposure to an array of organic compounds to determine whether contaminant-specific responses could be identified. The compounds investigated in contact tests included: two pesticides (carbaryl and chlorpyrifos), three pharmaceuticals (carbamazephine, estrone and caffeine), two persistent organohalogens (Aroclor 1254 and PBDE 209) and two industrial compounds (nonylphenol and dimethyl phthalate). Control and contaminant-exposed metabolic profiles were distinguished using principal component analysis and potential contaminant-specific biomarkers of exposure were found for several contaminants. These results suggest that NMR-based metabolomics offers considerable promise for differentiating between the different toxic modes of action (MOA) associated with sub-lethal toxicity to earthworms. - Highlights: → NMR-based earthworm metabolomic analysis of the toxic mode of action of various environmental contaminants. → Organic chemicals with different toxic modes of action resulted in varied metabolomic responses for E. fetida. → NMR-based metabolomics differentiates between the different modes of action associated with sub-lethal toxicity. - 1 H NMR metabolomics was used to identify potential biomarkers of organic contaminant exposure in Eisenia fetida earthworms.

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

DEFF Research Database (Denmark)

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

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

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

Directory of Open Access Journals (Sweden)

Laura Brugnara

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

HPLC-NMR revisited: Using time-slice HPLC-SPE-NMR with database assisted dereplication

DEFF Research Database (Denmark)

Johansen, Kenneth; Wubshet, Sileshi Gizachew; Nyberg, Nils

2013-01-01

Time based trapping of chromatographically separated compounds on to solid-phase extraction cartridges (SPE) and subsequent elution to NMR-tubes was done to emulate the function of HPLC–NMR for dereplication purposes. Sufficient mass sensitivity was obtained by the use of a state-of-the-art HPLC......–SPE–NMR-system with a cryogenically cooled probe head, designed for 1.7 mm NMR-tubes. The resulting 1H NMR spectra (600 MHz) were evaluated against a database of previously acquired and prepared spectra. The in-house developed matching algorithm, based on partitioning of the spectra and allowing for changes in the chemical shifts......, is described and the code included as Supplementary Information. Two mixtures of natural products was used to test the approach; one extract of Carthamus oxyacantha (wild safflower) containing an array of spiro compounds and one extract of the endophytic fungus Penicillum namyslowski containing griseofulvin...

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.

New dereplication method applied to NMR-Based metabolomics on different fusarium species isolated from Rhizosphere of Senna spectabilis

International Nuclear Information System (INIS)

Selegato, Denise M.; Castro-Gamboa, Ian; Freire, Rafael T.; Tannús, Alberto

2016-01-01

The search for new sources of natural products steadily increased the use of bioinformatics tools that enabled efficient analysis of complex matrices. In this context, dereplication methods emerged as a fast way of identifying known compounds, accelerating the identification of bioactive chemotypes. Although 1 H NMR is widely used as an analytical technique, few studies have been reported using it as a dereplication tool, primarily because of the spectral complexity. This work aims to create a new computational method that analyses 1 H NMR data from Fusarium solani and F. oxysporum isolated from Senna spectabilis' srhizosphere through principal component analysis (PCA). The algorithm uses loading values to select important peaks that distinguish both species in PCA, allowing compound dereplication, even in highly similar profiles. As a result, the method, associated with other NMR experiments and information from an in-house Fusarium's metabolite library was able to distinguish different mycotoxins produced by both fungi, identifying fusaric acid and beauvericin for F. oxysporum and the depsipeptide HA23 from F. solani. (author)

New dereplication method applied to NMR-Based metabolomics on different fusarium species isolated from Rhizosphere of Senna spectabilis

Energy Technology Data Exchange (ETDEWEB)

Selegato, Denise M.; Castro-Gamboa, Ian, E-mail: ian.castro@gmail.com [Universidade Estadual Paulista Júlio de Mesquita Filho (NuBBE/UNESP), Araraquara, SP (Brazil). Núcleo de Bioensaios, Biossíntese e Ecofisiologia de Produtos Naturais; Freire, Rafael T.; Tannús, Alberto [Universidade de São Paulo (CIERMag/USP), São Carlos, SP (Brazil). Centro de Imagens e Espectroscopia in Vivo por Ressonância Magnética

2016-07-01

The search for new sources of natural products steadily increased the use of bioinformatics tools that enabled efficient analysis of complex matrices. In this context, dereplication methods emerged as a fast way of identifying known compounds, accelerating the identification of bioactive chemotypes. Although {sup 1}H NMR is widely used as an analytical technique, few studies have been reported using it as a dereplication tool, primarily because of the spectral complexity. This work aims to create a new computational method that analyses {sup 1}H NMR data from Fusarium solani and F. oxysporum isolated from Senna spectabilis' srhizosphere through principal component analysis (PCA). The algorithm uses loading values to select important peaks that distinguish both species in PCA, allowing compound dereplication, even in highly similar profiles. As a result, the method, associated with other NMR experiments and information from an in-house Fusarium's metabolite library was able to distinguish different mycotoxins produced by both fungi, identifying fusaric acid and beauvericin for F. oxysporum and the depsipeptide HA23 from F. solani. (author)

NMR-based metabonomics and correlation analysis reveal potential biomarkers associated with chronic atrophic gastritis.

Science.gov (United States)

Cui, Jiajia; Liu, Yuetao; Hu, Yinghuan; Tong, Jiayu; Li, Aiping; Qu, Tingli; Qin, Xuemei; Du, Guanhua

2017-01-05

Chronic atrophic gastritis (CAG) is one of the most important pre-cancerous states with a high prevalence. Exploring of the underlying mechanism and potential biomarkers is of significant importance for CAG. In the present work, 1 H NMR-based metabonomics with correlative analysis was performed to analyze the metabolic features of CAG. 19 plasma metabolites and 18 urine metabolites were enrolled to construct the circulatory and excretory metabolome of CAG, which was in response to alterations of energy metabolism, inflammation, immune dysfunction, as well as oxidative stress. 7 plasma biomarkers and 7 urine biomarkers were screened to elucidate the pathogenesis of CAG based on the further correlation analysis with biochemical indexes. Finally, 3 plasma biomarkers (arginine, succinate and 3-hydroxybutyrate) and 2 urine biomarkers (α-ketoglutarate and valine) highlighted the potential to indicate risks of CAG in virtue of correlation with pepsin activity and ROC analysis. Here, our results paved a way for elucidating the underlying mechanisms in the development of CAG, and provided new avenues for the diagnosis of CAG and presented potential drug targets for treatment of CAG. Copyright © 2016 Elsevier B.V. All rights reserved.

Challenges in integrating component level technology and system level information from Ayurveda: Insights from NMR phytometabolomics and anti-HIV potential of select Ayurvedic medicinal plants.

Science.gov (United States)

Jayasundar, Rama; Ghatak, Somenath; Makhdoomi, Muzamil Ashraf; Luthra, Kalpana; Singh, Aruna; Velpandian, Thirumurthy

2018-01-03

Information from Ayurveda meeting the analytical challenges of modern technology is an area of immense relevance. Apart from the cerebral task of bringing together two different viewpoints, the question at the pragmatic level remains 'who benefits whom'. The aim is to highlight the challenges in integration of information (Ayurvedic) and technology using test examples of Nuclear Magnetic Resonance (NMR) metabolomics and anti-HIV-1 potential of select Ayurvedic medicinal plants. The other value added objective is implications and relevance of such work for Ayurveda. Six medicinal plants (Azadirachta indica, Tinospora cordifolia, Swertia chirata, Terminalia bellerica, Zingiber officinale and Symplocos racemosa) were studied using high resolution proton NMR spectroscopy based metabolomics and also evaluated for anti-HIV-1 activity on three pseudoviruses (ZM53 M.PB12, ZM109F.PB4, RHPA 4259.7). Of the six plants, T.bellerica and Z.officinale showed minimum cell cytotoxicity and maximum anti-HIV-1 potential. T.bellerica was effective against all the three HIV-1 pseudoviruses. Untargeted NMR profiling and multivariate analyses demonstrated that the six plants, all of which had different Ayurvedic pharmacological properties, showed maximum differences in the aromatic region of the spectra. The work adds onto the list of potential plants for anti-HIV-1 drug molecules. At the same time, it has drawn attention to the different perspectives of Ayurveda and Western medicine underscoring the inherent limitations of conceptual bilinguism between the two systems, especially in the context of medicinal plants. The study has also highlighted the potential of NMR metabolomics in study of plant extracts as used in Ayurveda. Copyright © 2017 Transdisciplinary University, Bangalore and World Ayurveda Foundation. Published by Elsevier B.V. All rights reserved.

Circadian Metabolomics in Time and Space

Directory of Open Access Journals (Sweden)

Kenneth A. Dyar

2017-07-01

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

Performance evaluation of tile-based Fisher Ratio analysis using a benchmark yeast metabolome dataset.

Science.gov (United States)

Watson, Nathanial E; Parsons, Brendon A; Synovec, Robert E

2016-08-12

Performance of tile-based Fisher Ratio (F-ratio) data analysis, recently developed for discovery-based studies using comprehensive two-dimensional gas chromatography coupled with time-of-flight mass spectrometry (GC×GC-TOFMS), is evaluated with a metabolomics dataset that had been previously analyzed in great detail, but while taking a brute force approach. The previously analyzed data (referred to herein as the benchmark dataset) were intracellular extracts from Saccharomyces cerevisiae (yeast), either metabolizing glucose (repressed) or ethanol (derepressed), which define the two classes in the discovery-based analysis to find metabolites that are statistically different in concentration between the two classes. Beneficially, this previously analyzed dataset provides a concrete means to validate the tile-based F-ratio software. Herein, we demonstrate and validate the significant benefits of applying tile-based F-ratio analysis. The yeast metabolomics data are analyzed more rapidly in about one week versus one year for the prior studies with this dataset. Furthermore, a null distribution analysis is implemented to statistically determine an adequate F-ratio threshold, whereby the variables with F-ratio values below the threshold can be ignored as not class distinguishing, which provides the analyst with confidence when analyzing the hit table. Forty-six of the fifty-four benchmarked changing metabolites were discovered by the new methodology while consistently excluding all but one of the benchmarked nineteen false positive metabolites previously identified. Copyright © 2016 Elsevier B.V. All rights reserved.

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

Science.gov (United States)

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

2015-12-01

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

The influence of different diets on metabolism and atherosclerosis processes-A porcine model: Blood serum, urine and tissues 1H NMR metabolomics targeted analysis.

Directory of Open Access Journals (Sweden)

Adam Zabek

Full Text Available The global epidemic of cardiovascular diseases leads to increased morbidity and mortality caused mainly by myocardial infarction and stroke. Atherosclerosis is the major pathological process behind this epidemic. We designed a novel model of atherosclerosis in swine. Briefly, the first group (11 pigs received normal pig feed (balanced diet group-BDG for 12 months, the second group (9 pigs was fed a Western high-calorie diet (unbalanced diet group-UDG for 12 months, the third group (8 pigs received a Western type high-calorie diet for 9 months later replaced by a normal diet for 3 months (regression group-RG. Clinical measurements included zoometric data, arterial blood pressure, heart rate and ultrasonographic evaluation of femoral arteries. Then, the animals were sacrificed and the blood serum, urine and skeletal muscle tissue were collected and 1H NMR based metabolomics studies with the application of fingerprinting PLS-DA and univariate analysis were done. Our results have shown that the molecular disturbances might overlap with other diseases such as onset of diabetes, sleep apnea and other obesity accompanied diseases. Moreover, we revealed that once initiated, molecular changes did not return to homeostatic equilibrium, at least for the duration of this experiment.

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

Science.gov (United States)

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

2016-01-05

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

Intra- and inter-metabolite correlation spectroscopy of tomato metabolomics data obtained by liquid chromatography-mass spectrometry and nuclear magnetic resonance

NARCIS (Netherlands)

Moco, S.I.A.; Forshed, J.; Vos, de C.H.; Bino, R.J.; Vervoort, J.J.M.

2008-01-01

Nuclear magnetic resonance (NMR) and liquid chromatography-mass spectrometry (LCMS) are frequently used as technological platforms for metabolomics applications. In this study, the metabolic profiles of ripe fruits from 50 different tomato cultivars, including beef, cherry and round types, were

Hepatitis B virus X protein (HBx)-induced abnormalities of nucleic acid metabolism revealed by (1)H-NMR-based metabonomics.

Science.gov (United States)

Dan Yue; Zhang, Yuwei; Cheng, Liuliu; Ma, Jinhu; Xi, Yufeng; Yang, Liping; Su, Chao; Shao, Bin; Huang, Anliang; Xiang, Rong; Cheng, Ping

2016-04-14

Hepatitis B virus X protein (HBx) plays an important role in HBV-related hepatocarcinogenesis; however, mechanisms underlying HBx-mediated carcinogenesis remain unclear. In this study, an NMR-based metabolomics approach was applied to systematically investigate the effects of HBx on cell metabolism. EdU incorporation assay was conducted to examine the effects of HBx on DNA synthesis, an important feature of nucleic acid metabolism. The results revealed that HBx disrupted metabolism of glucose, lipids, and amino acids, especially nucleic acids. To understand the potential mechanism of HBx-induced abnormalities of nucleic acid metabolism, gene expression profiles of HepG2 cells expressing HBx were investigated. The results showed that 29 genes involved in DNA damage and DNA repair were differentially expressed in HBx-expressing HepG2 cells. HBx-induced DNA damage was further demonstrated by karyotyping, comet assay, Western blotting, immunofluorescence and immunohistochemistry analyses. Many studies have previously reported that DNA damage can induce abnormalities of nucleic acid metabolism. Thus, our results implied that HBx initially induces DNA damage, and then disrupts nucleic acid metabolism, which in turn blocks DNA repair and induces the occurrence of hepatocellular carcinoma (HCC). These findings further contribute to our understanding of the occurrence of HCC.

Metabolomics in the fight against malaria

Directory of Open Access Journals (Sweden)

Jorge L Salinas

2014-08-01

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

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.

The effect of acyclic retinoid on the metabolomic profiles of hepatocytes and hepatocellular carcinoma cells.

Directory of Open Access Journals (Sweden)

Xian-Yang Qin

Full Text Available BACKGROUND/PURPOSE: Acyclic retinoid (ACR is a promising chemopreventive agent for hepatocellular carcinoma (HCC that selectively inhibits the growth of HCC cells (JHH7 but not normal hepatic cells (Hc. To better understand the molecular basis of the selective anti-cancer effect of ACR, we performed nuclear magnetic resonance (NMR-based and capillary electrophoresis time-of-flight mass spectrometry (CE-TOFMS-based metabolome analyses in JHH7 and Hc cells after treatment with ACR. METHODOLOGY/PRINCIPAL FINDINGS: NMR-based metabolomics revealed a distinct metabolomic profile of JHH7 cells at 18 h after ACR treatment but not at 4 h after ACR treatment. CE-TOFMS analysis identified 88 principal metabolites in JHH7 and Hc cells after 24 h of treatment with ethanol (EtOH or ACR. The abundance of 71 of these metabolites was significantly different between EtOH-treated control JHH7 and Hc cells, and 49 of these metabolites were significantly down-regulated in the ACR-treated JHH7 cells compared to the EtOH-treated JHH7 cells. Of particular interest, the increase in adenosine-5'-triphosphate (ATP, the main cellular energy source, that was observed in the EtOH-treated control JHH7 cells was almost completely suppressed in the ACR-treated JHH7 cells; treatment with ACR restored ATP to the basal levels observed in both EtOH-control and ACR-treated Hc cells (0.72-fold compared to the EtOH control-treated JHH7 cells. Moreover, real-time PCR analyses revealed that ACR significantly increased the expression of pyruvate dehydrogenase kinases 4 (PDK4, a key regulator of ATP production, in JHH7 cells but not in Hc cells (3.06-fold and 1.20-fold compared to the EtOH control, respectively. CONCLUSIONS/SIGNIFICANCE: The results of the present study suggest that ACR may suppress the enhanced energy metabolism of JHH7 cells but not Hc cells; this occurs at least in part via the cancer-selective enhancement of PDK4 expression. The cancer-selective metabolic pathways