The 1H-NMR-based metabolite profile of acute alcohol consumption: A metabolomics intervention study

PubMed Central

Mason, Shayne; Mienie, Lodewyk J.; Wevers, Ron A.; Westerhuis, Johan A.

2018-01-01

Metabolomics studies of disease conditions related to chronic alcohol consumption provide compelling evidence of several perturbed metabolic pathways underlying the pathophysiology of alcoholism. The objective of the present study was to utilize proton nuclear magnetic resonance (1H-NMR) spectroscopy metabolomics to study the holistic metabolic consequences of acute alcohol consumption in humans. The experimental design was a cross-over intervention study which included a number of substances to be consumed—alcohol, a nicotinamide adenine dinucleotide (NAD) supplement, and a benzoic acid-containing flavoured water vehicle. The experimental subjects—24 healthy, moderate-drinking young men—each provided six hourly-collected urine samples for analysis. Complete data sets were obtained from 20 of the subjects and used for data generation, analysis and interpretation. The results from the NMR approach produced complex spectral data, which could be resolved sufficiently through the application of a combination of univariate and multivariate methods of statistical analysis. The metabolite profiles resulting from acute alcohol consumption indicated that alcohol-induced NAD+ depletion, and the production of an excessive amount of reducing equivalents, greatly perturbed the hepatocyte redox homeostasis, resulting in essentially three major metabolic disturbances—up-regulated lactic acid metabolism, down-regulated purine catabolism and osmoregulation. Of these, the urinary excretion of the osmolyte sorbitol proved to be novel, and suggests hepatocyte swelling due to ethanol influx following acute alcohol consumption. Time-dependent metabolomics investigations, using designed interventions, provide a way of interpreting the variation induced by the different factors of a designed experiment, thereby also giving methodological significance to this study. The outcomes of this approach have the potential to significantly advance our understanding of the serious impact of the pathophysiological perturbations which arise from the consumption of a single, large dose of alcohol—a simulation of a widespread, and mostly naive, social practice. PMID:29746531

MeRy-B: a web knowledgebase for the storage, visualization, analysis and annotation of plant NMR metabolomic profiles

PubMed Central

2011-01-01

Background Improvements in the techniques for metabolomics analyses and growing interest in metabolomic approaches are resulting in the generation of increasing numbers of metabolomic profiles. Platforms are required for profile management, as a function of experimental design, and for metabolite identification, to facilitate the mining of the corresponding data. Various databases have been created, including organism-specific knowledgebases and analytical technique-specific spectral databases. However, there is currently no platform meeting the requirements for both profile management and metabolite identification for nuclear magnetic resonance (NMR) experiments. Description MeRy-B, the first platform for plant 1H-NMR metabolomic profiles, is designed (i) to provide a knowledgebase of curated plant profiles and metabolites obtained by NMR, together with the corresponding experimental and analytical metadata, (ii) for queries and visualization of the data, (iii) to discriminate between profiles with spectrum visualization tools and statistical analysis, (iv) to facilitate compound identification. It contains lists of plant metabolites and unknown compounds, with information about experimental conditions, the factors studied and metabolite concentrations for several plant species, compiled from more than one thousand annotated NMR profiles for various organs or tissues. Conclusion MeRy-B manages all the data generated by NMR-based plant metabolomics experiments, from description of the biological source to identification of the metabolites and determinations of their concentrations. It is the first database allowing the display and overlay of NMR metabolomic profiles selected through queries on data or metadata. MeRy-B is available from http://www.cbib.u-bordeaux2.fr/MERYB/index.php. PMID:21668943

Comprehensive metabolomic profiling and incident cardiovascular disease: a systematic review

USDA-ARS?s Scientific Manuscript database

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

Non-invasive urinary metabolomic profiling discriminates prostate cancer from benign prostatic hyperplasia.

PubMed

Pérez-Rambla, Clara; Puchades-Carrasco, Leonor; García-Flores, María; Rubio-Briones, José; López-Guerrero, José Antonio; Pineda-Lucena, Antonio

2017-01-01

Prostate cancer (PCa) is one of the most common malignancies in men worldwide. Serum prostate specific antigen (PSA) level has been extensively used as a biomarker to detect PCa. However, PSA is not cancer-specific and various non-malignant conditions, including benign prostatic hyperplasia (BPH), can cause a rise in PSA blood levels, thus leading to many false positive results. In this study, we evaluated the potential of urinary metabolomic profiling for discriminating PCa from BPH. Urine samples from 64 PCa patients and 51 individuals diagnosed with BPH were analysed using 1 H nuclear magnetic resonance ( 1 H-NMR). Comparative analysis of urinary metabolomic profiles was carried out using multivariate and univariate statistical approaches. The urine metabolomic profile of PCa patients is characterised by increased concentrations of branched-chain amino acids (BCAA), glutamate and pseudouridine, and decreased concentrations of glycine, dimethylglycine, fumarate and 4-imidazole-acetate compared with individuals diagnosed with BPH. PCa patients have a specific urinary metabolomic profile. The results of our study underscore the clinical potential of metabolomic profiling to uncover metabolic changes that could be useful to discriminate PCa from BPH in a clinical context.

Metabolomic profiles as reliable biomarkers of dietary composition123

PubMed Central

Esko, Tõnu; Hirschhorn, Joel N; Feldman, Henry A; Hsu, Yu-Han H; Deik, Amy A; Clish, Clary B; Ebbeling, Cara B; Ludwig, David S

2017-01-01

Background: Clinical nutrition research often lacks robust markers of compliance, complicating the interpretation of clinical trials and observational studies of free-living subjects. Objective: We aimed to examine metabolomics profiles in response to 3 diets that differed widely in macronutrient composition during a controlled feeding protocol. Design: Twenty-one adults with a high body mass index (in kg/m2; mean ± SD: 34.4 ± 4.9) were given hypocaloric diets to promote weight loss corresponding to 10–15% of initial body weight. They were then studied during weight stability while consuming 3 test diets, each for a 4-wk period according to a crossover design: low fat (60% carbohydrate, 20% fat, 20% protein), low glycemic index (40% carbohydrate, 40% fat, 20% protein), or very-low carbohydrate (10% carbohydrate, 60% fat, 30% protein). Plasma samples were obtained at baseline and at the end of each 4-wk period in the fasting state for metabolomics analysis by using liquid chromatography–tandem mass spectrometry. Statistical analyses included adjustment for multiple comparisons. Results: Of 333 metabolites, we identified 152 whose concentrations differed for ≥1 diet compared with the others, including diacylglycerols and triacylglycerols, branched-chain amino acids, and markers reflecting metabolic status. Analysis of groups of related metabolites, with the use of either principal components or pathways, revealed coordinated metabolic changes affected by dietary composition, including pathways related to amino acid metabolism. We constructed a classifier using the metabolites that differed between diets and were able to correctly identify the test diet from metabolite profiles in 60 of 63 cases (>95% accuracy). Analyses also suggest differential effects by diet on numerous cardiometabolic disease risk factors. Conclusions: Metabolomic profiling may be used to assess compliance during clinical nutrition trials and the validity of dietary assessment in observational studies. In addition, this methodology may help elucidate mechanistic pathways linking diet to chronic disease risk. This trial was registered at clinicaltrials.gov as NCT00315354. PMID:28077380

Metabolomic profiles as reliable biomarkers of dietary composition.

PubMed

Esko, Tõnu; Hirschhorn, Joel N; Feldman, Henry A; Hsu, Yu-Han H; Deik, Amy A; Clish, Clary B; Ebbeling, Cara B; Ludwig, David S

2017-03-01

Background: Clinical nutrition research often lacks robust markers of compliance, complicating the interpretation of clinical trials and observational studies of free-living subjects. Objective: We aimed to examine metabolomics profiles in response to 3 diets that differed widely in macronutrient composition during a controlled feeding protocol. Design: Twenty-one adults with a high body mass index (in kg/m 2 ; mean ± SD: 34.4 ± 4.9) were given hypocaloric diets to promote weight loss corresponding to 10-15% of initial body weight. They were then studied during weight stability while consuming 3 test diets, each for a 4-wk period according to a crossover design: low fat (60% carbohydrate, 20% fat, 20% protein), low glycemic index (40% carbohydrate, 40% fat, 20% protein), or very-low carbohydrate (10% carbohydrate, 60% fat, 30% protein). Plasma samples were obtained at baseline and at the end of each 4-wk period in the fasting state for metabolomics analysis by using liquid chromatography-tandem mass spectrometry. Statistical analyses included adjustment for multiple comparisons. Results: Of 333 metabolites, we identified 152 whose concentrations differed for ≥1 diet compared with the others, including diacylglycerols and triacylglycerols, branched-chain amino acids, and markers reflecting metabolic status. Analysis of groups of related metabolites, with the use of either principal components or pathways, revealed coordinated metabolic changes affected by dietary composition, including pathways related to amino acid metabolism. We constructed a classifier using the metabolites that differed between diets and were able to correctly identify the test diet from metabolite profiles in 60 of 63 cases (>95% accuracy). Analyses also suggest differential effects by diet on numerous cardiometabolic disease risk factors. Conclusions: Metabolomic profiling may be used to assess compliance during clinical nutrition trials and the validity of dietary assessment in observational studies. In addition, this methodology may help elucidate mechanistic pathways linking diet to chronic disease risk. This trial was registered at clinicaltrials.gov as NCT00315354. © 2017 American Society for Nutrition.

NMR and MS Methods for Metabolomics.

PubMed

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

2017-01-01

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

Biomarker analysis of American toad (Anaxyrus americanus) ...

EPA Pesticide Factsheets

The objective of the current study was to use a biomarker-based approach to investigate the influence of atrazine exposure on American toad (Anaxyrus americanus) and grey tree frog (Hyla versicolor) tadpoles. Atrazine is one of the most frequently detected herbicides in environmental matrices throughout the United States. In surface waters, it has been found at concentrations from 0.04–2859 μg/L and thus presents a likely exposure scenario for non-target species such as amphibians. Studies have examined the effect of atrazine on the metamorphic parameters of amphibians, however, the data are often contradictory. Gosner stage 22–24 tadpoles were exposed to 0 (control), 10, 50, 250 or 1250 μg/L of atrazine for 48 h. Endogenous polar metabolites were extracted and analyzed using gas chromatography coupled with mass spectrometry. Statistical analyses of the acquired spectra with machine learning classification models demonstrated identifiable changes in the metabolomic profiles between exposed and control tadpoles. Support vector machine models with recursive feature elimination created a more efficient, non-parametric data analysis and increased interpretability of metabolomic profiles. Biochemical fluxes observed in the exposed groups of both A. americanus and H. versicolor displayed perturbations in a number of classes of biological macromolecules including fatty acids, amino acids, purine nucleosides, pyrimidines, and mono- and di-saccharides. Metabolomic

Digging into the low molecular weight peptidome with the OligoNet web server.

PubMed

Liu, Youzhong; Forcisi, Sara; Lucio, Marianna; Harir, Mourad; Bahut, Florian; Deleris-Bou, Magali; Krieger-Weber, Sibylle; Gougeon, Régis D; Alexandre, Hervé; Schmitt-Kopplin, Philippe

2017-09-15

Bioactive peptides play critical roles in regulating many biological processes. Recently, natural short peptides biomarkers are drawing significant attention and are considered as "hidden treasure" of drug candidates. High resolution and high mass accuracy provided by mass spectrometry (MS)-based untargeted metabolomics would enable the rapid detection and wide coverage of the low-molecular-weight peptidome. However, translating unknown masses (<1 500 Da) into putative peptides is often limited due to the lack of automatic data processing tools and to the limit of peptide databases. The web server OligoNet responds to this challenge by attempting to decompose each individual mass into a combination of amino acids out of metabolomics datasets. It provides an additional network-based data interpretation named "Peptide degradation network" (PDN), which unravels interesting relations between annotated peptides and generates potential functional patterns. The ab initio PDN built from yeast metabolic profiling data shows a great similarity with well-known metabolic networks, and could aid biological interpretation. OligoNet allows also an easy evaluation and interpretation of annotated peptides in systems biology, and is freely accessible at https://daniellyz200608105.shinyapps.io/OligoNet/ .

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

PubMed

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

2018-09-26

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

Differential metabolic profiles associated to movement behaviour of stream-resident brown trout (Salmo trutta).

PubMed

Oromi, Neus; Jové, Mariona; Pascual-Pons, Mariona; Royo, Jose Luis; Rocaspana, Rafel; Aparicio, Enric; Pamplona, Reinald; Palau, Antoni; Sanuy, Delfi; Fibla, Joan; Portero-Otin, Manuel

2017-01-01

The mechanisms that can contribute in the fish movement strategies and the associated behaviour can be complex and related to the physiology, genetic and ecology of each species. In the case of the brown trout (Salmo trutta), in recent research works, individual differences in mobility have been observed in a population living in a high mountain river reach (Pyrenees, NE Spain). The population is mostly sedentary but a small percentage of individuals exhibit a mobile behavior, mainly upstream movements. Metabolomics can reflect changes in the physiological process and can determine different profiles depending on behaviour. Here, a non-targeted metabolomics approach was used to find possible changes in the blood metabolomic profile of S. trutta related to its movement behaviour, using a minimally invasive sampling. Results showed a differentiation in the metabolomic profiles of the trouts and different level concentrations of some metabolites (e.g. cortisol) according to the home range classification (pattern of movements: sedentary or mobile). The change in metabolomic profiles can generally occur during the upstream movement and probably reflects the changes in metabolite profile from the non-mobile season to mobile season. This study reveals the contribution of the metabolomic analyses to better understand the behaviour of organisms.

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

PubMed

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.

A global approach to analysis and interpretation of metabolic data for plant natural product discovery.

PubMed

Hur, Manhoi; Campbell, Alexis Ann; Almeida-de-Macedo, Marcia; Li, Ling; Ransom, Nick; Jose, Adarsh; Crispin, Matt; Nikolau, Basil J; Wurtele, Eve Syrkin

2013-04-01

Discovering molecular components and their functionality is key to the development of hypotheses concerning the organization and regulation of metabolic networks. The iterative experimental testing of such hypotheses is the trajectory that can ultimately enable accurate computational modelling and prediction of metabolic outcomes. This information can be particularly important for understanding the biology of natural products, whose metabolism itself is often only poorly defined. Here, we describe factors that must be in place to optimize the use of metabolomics in predictive biology. A key to achieving this vision is a collection of accurate time-resolved and spatially defined metabolite abundance data and associated metadata. One formidable challenge associated with metabolite profiling is the complexity and analytical limits associated with comprehensively determining the metabolome of an organism. Further, for metabolomics data to be efficiently used by the research community, it must be curated in publicly available metabolomics databases. Such databases require clear, consistent formats, easy access to data and metadata, data download, and accessible computational tools to integrate genome system-scale datasets. Although transcriptomics and proteomics integrate the linear predictive power of the genome, the metabolome represents the nonlinear, final biochemical products of the genome, which results from the intricate system(s) that regulate genome expression. For example, the relationship of metabolomics data to the metabolic network is confounded by redundant connections between metabolites and gene-products. However, connections among metabolites are predictable through the rules of chemistry. Therefore, enhancing the ability to integrate the metabolome with anchor-points in the transcriptome and proteome will enhance the predictive power of genomics data. We detail a public database repository for metabolomics, tools and approaches for statistical analysis of metabolomics data, and methods for integrating these datasets with transcriptomic data to create hypotheses concerning specialized metabolisms that generate the diversity in natural product chemistry. We discuss the importance of close collaborations among biologists, chemists, computer scientists and statisticians throughout the development of such integrated metabolism-centric databases and software.

A global approach to analysis and interpretation of metabolic data for plant natural product discovery†

PubMed Central

Hur, Manhoi; Campbell, Alexis Ann; Almeida-de-Macedo, Marcia; Li, Ling; Ransom, Nick; Jose, Adarsh; Crispin, Matt; Nikolau, Basil J.

2013-01-01

Discovering molecular components and their functionality is key to the development of hypotheses concerning the organization and regulation of metabolic networks. The iterative experimental testing of such hypotheses is the trajectory that can ultimately enable accurate computational modelling and prediction of metabolic outcomes. This information can be particularly important for understanding the biology of natural products, whose metabolism itself is often only poorly defined. Here, we describe factors that must be in place to optimize the use of metabolomics in predictive biology. A key to achieving this vision is a collection of accurate time-resolved and spatially defined metabolite abundance data and associated metadata. One formidable challenge associated with metabolite profiling is the complexity and analytical limits associated with comprehensively determining the metabolome of an organism. Further, for metabolomics data to be efficiently used by the research community, it must be curated in publically available metabolomics databases. Such databases require clear, consistent formats, easy access to data and metadata, data download, and accessible computational tools to integrate genome system-scale datasets. Although transcriptomics and proteomics integrate the linear predictive power of the genome, the metabolome represents the nonlinear, final biochemical products of the genome, which results from the intricate system(s) that regulate genome expression. For example, the relationship of metabolomics data to the metabolic network is confounded by redundant connections between metabolites and gene-products. However, connections among metabolites are predictable through the rules of chemistry. Therefore, enhancing the ability to integrate the metabolome with anchor-points in the transcriptome and proteome will enhance the predictive power of genomics data. We detail a public database repository for metabolomics, tools and approaches for statistical analysis of metabolomics data, and methods for integrating these dataset with transcriptomic data to create hypotheses concerning specialized metabolism that generates the diversity in natural product chemistry. We discuss the importance of close collaborations among biologists, chemists, computer scientists and statisticians throughout the development of such integrated metabolism-centric databases and software. PMID:23447050

Highlights of the 2012 Research Workshop: Using nutrigenomics and metabolomics in clinical nutrition research.

PubMed

Zeisel, Steven H; Waterland, Robert A; Ordovás, José M; Muoio, Deborah M; Jia, Wei; Fodor, Anthony

2013-03-01

The American Society for Parenteral and Enteral Nutrition (A.S.P.E.N.) Research Workshop, "Using Nutrigenomics and Metabolomics in Clinical Nutrition Research," was held on January 21, 2012, in Orlando, Florida. The conference brought together experts in human nutrition who use nutrigenomic and metabolomic methods to better understand metabolic individuality and nutrition effects on health. We are beginning to understand how genetic variation and epigenetic events alter requirements for and responses to foods in our diet (the field of nutrigenetics/nutrigenomics and epigenetics). At the same time, methods for profiling almost all of the products of metabolism in plasma, urine, and tissues (metabolomics) are being refined. The relationships between diet and nutrigenomic-metabolomic profiles, as well as between these profiles and health, are being elucidated, and this will dramatically alter clinical practice in nutrition.

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

PubMed

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

2016-01-01

Multiple molecular assays now enable high-throughput profiling of the ecology, metabolic capacity, and activity of the human microbiome. However, to date, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms linking these various facets of the microbiome. Here, we introduce a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, we integrate available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community. Our framework then compares variation in predicted metabolic potential with variation in measured metabolites' abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts. Focusing on two independent vaginal microbiome data sets, each pairing 16S community profiling with large-scale metabolomics, we demonstrate that our framework successfully recapitulates observed variation in 37% of metabolites. Well-predicted metabolite variation tends to result from disease-associated metabolism. We further identify several disease-enriched species that contribute significantly to these predictions. Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism. Applying this framework to gut microbiome data sets reveals similar trends, including prediction of bile acid metabolite shifts. This framework is an important first step toward a system-level multi-omic integration and an improved mechanistic understanding of the microbiome activity and dynamics in health and disease. Studies characterizing both the taxonomic composition and metabolic profile of various microbial communities are becoming increasingly common, yet new computational methods are needed to integrate and interpret these data in terms of known biological mechanisms. Here, we introduce an analytical framework to link species composition and metabolite measurements, using a simple model to predict the effects of community ecology on metabolite concentrations and evaluating whether these predictions agree with measured metabolomic profiles. We find that a surprisingly large proportion of metabolite variation in the vaginal microbiome can be predicted based on species composition (including dramatic shifts associated with disease), identify putative mechanisms underlying these predictions, and evaluate the roles of individual bacterial species and genes. Analysis of gut microbiome data using this framework recovers similar community metabolic trends. This framework lays the foundation for model-based multi-omic integrative studies, ultimately improving our understanding of microbial community metabolism.

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

PubMed Central

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

2016-01-01

ABSTRACT Multiple molecular assays now enable high-throughput profiling of the ecology, metabolic capacity, and activity of the human microbiome. However, to date, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms linking these various facets of the microbiome. Here, we introduce a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, we integrate available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community. Our framework then compares variation in predicted metabolic potential with variation in measured metabolites’ abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts. Focusing on two independent vaginal microbiome data sets, each pairing 16S community profiling with large-scale metabolomics, we demonstrate that our framework successfully recapitulates observed variation in 37% of metabolites. Well-predicted metabolite variation tends to result from disease-associated metabolism. We further identify several disease-enriched species that contribute significantly to these predictions. Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism. Applying this framework to gut microbiome data sets reveals similar trends, including prediction of bile acid metabolite shifts. This framework is an important first step toward a system-level multi-omic integration and an improved mechanistic understanding of the microbiome activity and dynamics in health and disease. IMPORTANCE Studies characterizing both the taxonomic composition and metabolic profile of various microbial communities are becoming increasingly common, yet new computational methods are needed to integrate and interpret these data in terms of known biological mechanisms. Here, we introduce an analytical framework to link species composition and metabolite measurements, using a simple model to predict the effects of community ecology on metabolite concentrations and evaluating whether these predictions agree with measured metabolomic profiles. We find that a surprisingly large proportion of metabolite variation in the vaginal microbiome can be predicted based on species composition (including dramatic shifts associated with disease), identify putative mechanisms underlying these predictions, and evaluate the roles of individual bacterial species and genes. Analysis of gut microbiome data using this framework recovers similar community metabolic trends. This framework lays the foundation for model-based multi-omic integrative studies, ultimately improving our understanding of microbial community metabolism. PMID:27239563

Enabling Efficient and Confident Annotation of LC−MS Metabolomics Data through MS1 Spectrum and Time Prediction

DOE PAGES

Broeckling, Corey D.; Ganna, Andrea; Layer, Mark; ...

2016-09-08

Liquid chromatography coupled to electrospray ionization-mass spectrometry (LC–ESI-MS) is a versatile and robust platform for metabolomic analysis. However, while ESI is a soft ionization technique, in-source phenomena including multimerization, nonproton cation adduction, and in-source fragmentation complicate interpretation of MS data. Here, we report chromatographic and mass spectrometric behavior of 904 authentic standards collected under conditions identical to a typical nontargeted profiling experiment. The data illustrate that the often high level of complexity in MS spectra is likely to result in misinterpretation during the annotation phase of the experiment and a large overestimation of the number of compounds detected. However, ourmore » analysis of this MS spectral library data indicates that in-source phenomena are not random but depend at least in part on chemical structure. These nonrandom patterns enabled predictions to be made as to which in-source signals are likely to be observed for a given compound. Using the authentic standard spectra as a training set, we modeled the in-source phenomena for all compounds in the Human Metabolome Database to generate a theoretical in-source spectrum and retention time library. A novel spectral similarity matching platform was developed to facilitate efficient spectral searching for nontargeted profiling applications. Taken together, this collection of experimental spectral data, predictive modeling, and informatic tools enables more efficient, reliable, and transparent metabolite annotation.« less

Enabling Efficient and Confident Annotation of LC-MS Metabolomics Data through MS1 Spectrum and Time Prediction

DOE PAGES

Broeckling, Corey D.; Ganna, Andrea; Layer, Mark; ...

2016-08-25

Liquid chromatography coupled to electrospray ionization-mass spectrometry (LC–ESI-MS) is a versatile and robust platform for metabolomic analysis. However, while ESI is a soft ionization technique, in-source phenomena including multimerization, nonproton cation adduction, and in-source fragmentation complicate interpretation of MS data. Here, we report chromatographic and mass spectrometric behavior of 904 authentic standards collected under conditions identical to a typical nontargeted profiling experiment. The data illustrate that the often high level of complexity in MS spectra is likely to result in misinterpretation during the annotation phase of the experiment and a large overestimation of the number of compounds detected. However, ourmore » analysis of this MS spectral library data indicates that in-source phenomena are not random but depend at least in part on chemical structure. These nonrandom patterns enabled predictions to be made as to which in-source signals are likely to be observed for a given compound. Using the authentic standard spectra as a training set, we modeled the in-source phenomena for all compounds in the Human Metabolome Database to generate a theoretical in-source spectrum and retention time library. A novel spectral similarity matching platform was developed to facilitate efficient spectral searching for nontargeted profiling applications. Taken together, this collection of experimental spectral data, predictive modeling, and informatic tools enables more efficient, reliable, and transparent metabolite annotation.« less

A Comprehensive Strategy to Construct In-house Database for Accurate and Batch Identification of Small Molecular Metabolites.

PubMed

Zhao, Xinjie; Zeng, Zhongda; Chen, Aiming; Lu, Xin; Zhao, Chunxia; Hu, Chunxiu; Zhou, Lina; Liu, Xinyu; Wang, Xiaolin; Hou, Xiaoli; Ye, Yaorui; Xu, Guowang

2018-05-29

Identification of the metabolites is an essential step in metabolomics study to interpret regulatory mechanism of pathological and physiological processes. However, it is still a big headache in LC-MSn-based studies because of the complexity of mass spectrometry, chemical diversity of metabolites, and deficiency of standards database. In this work, a comprehensive strategy is developed for accurate and batch metabolite identification in non-targeted metabolomics studies. First, a well defined procedure was applied to generate reliable and standard LC-MS2 data including tR, MS1 and MS2 information at a standard operational procedure (SOP). An in-house database including about 2000 metabolites was constructed and used to identify the metabolites in non-targeted metabolic profiling by retention time calibration using internal standards, precursor ion alignment and ion fusion, auto-MS2 information extraction and selection, and database batch searching and scoring. As an application example, a pooled serum sample was analyzed to deliver the strategy, 202 metabolites were identified in the positive ion mode. It shows our strategy is useful for LC-MSn-based non-targeted metabolomics study.

Spectroscopic and Statistical Techniques for Information Recovery in Metabonomics and Metabolomics

NASA Astrophysics Data System (ADS)

Lindon, John C.; Nicholson, Jeremy K.

2008-07-01

Methods for generating and interpreting metabolic profiles based on nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry (MS), and chemometric analysis methods are summarized and the relative strengths and weaknesses of NMR and chromatography-coupled MS approaches are discussed. Given that all data sets measured to date only probe subsets of complex metabolic profiles, we describe recent developments for enhanced information recovery from the resulting complex data sets, including integration of NMR- and MS-based metabonomic results and combination of metabonomic data with data from proteomics, transcriptomics, and genomics. We summarize the breadth of applications, highlight some current activities, discuss the issues relating to metabonomics, and identify future trends.

Spectroscopic and statistical techniques for information recovery in metabonomics and metabolomics.

PubMed

Lindon, John C; Nicholson, Jeremy K

2008-01-01

Methods for generating and interpreting metabolic profiles based on nuclear magnetic resonance (NMR) spectroscopy, mass spectrometry (MS), and chemometric analysis methods are summarized and the relative strengths and weaknesses of NMR and chromatography-coupled MS approaches are discussed. Given that all data sets measured to date only probe subsets of complex metabolic profiles, we describe recent developments for enhanced information recovery from the resulting complex data sets, including integration of NMR- and MS-based metabonomic results and combination of metabonomic data with data from proteomics, transcriptomics, and genomics. We summarize the breadth of applications, highlight some current activities, discuss the issues relating to metabonomics, and identify future trends.

Rule-Mining for the Early Prediction of Chronic Kidney Disease Based on Metabolomics and Multi-Source Data

PubMed Central

Luck, Margaux; Bertho, Gildas; Bateson, Mathilde; Karras, Alexandre; Yartseva, Anastasia; Thervet, Eric

2016-01-01

1H Nuclear Magnetic Resonance (NMR)-based metabolic profiling is very promising for the diagnostic of the stages of chronic kidney disease (CKD). Because of the high dimension of NMR spectra datasets and the complex mixture of metabolites in biological samples, the identification of discriminant biomarkers of a disease is challenging. None of the widely used chemometric methods in NMR metabolomics performs a local exhaustive exploration of the data. We developed a descriptive and easily understandable approach that searches for discriminant local phenomena using an original exhaustive rule-mining algorithm in order to predict two groups of patients: 1) patients having low to mild CKD stages with no renal failure and 2) patients having moderate to established CKD stages with renal failure. Our predictive algorithm explores the m-dimensional variable space to capture the local overdensities of the two groups of patients under the form of easily interpretable rules. Afterwards, a L2-penalized logistic regression on the discriminant rules was used to build predictive models of the CKD stages. We explored a complex multi-source dataset that included the clinical, demographic, clinical chemistry, renal pathology and urine metabolomic data of a cohort of 110 patients. Given this multi-source dataset and the complex nature of metabolomic data, we analyzed 1- and 2-dimensional rules in order to integrate the information carried by the interactions between the variables. The results indicated that our local algorithm is a valuable analytical method for the precise characterization of multivariate CKD stage profiles and as efficient as the classical global model using chi2 variable section with an approximately 70% of good classification level. The resulting predictive models predominantly identify urinary metabolites (such as 3-hydroxyisovalerate, carnitine, citrate, dimethylsulfone, creatinine and N-methylnicotinamide) as relevant variables indicating that CKD significantly affects the urinary metabolome. In addition, the simple knowledge of the concentration of urinary metabolites classifies the CKD stage of the patients correctly. PMID:27861591

Effect of masticatory stimulation on the quantity and quality of saliva and the salivary metabolomic profile.

PubMed

Okuma, Nobuyuki; Saita, Makiko; Hoshi, Noriyuki; Soga, Tomoyoshi; Tomita, Masaru; Sugimoto, Masahiro; Kimoto, Katsuhiko

2017-01-01

This study characterized the changes in quality and quantity of saliva, and changes in the salivary metabolomic profile, to understand the effects of masticatory stimulation. Stimulated and unstimulated saliva samples were collected from 55 subjects and salivary hydrophilic metabolites were comprehensively quantified using capillary electrophoresis-time-of-flight mass spectrometry. In total, 137 metabolites were identified and quantified. The concentrations of 44 metabolites in stimulated saliva were significantly higher than those in unstimulated saliva. Pathway analysis identified the upregulation of the urea cycle and synthesis and degradation pathways of glycine, serine, cysteine and threonine in stimulated saliva. A principal component analysis revealed that the effect of masticatory stimulation on salivary metabolomic profiles was less dependent on sample population sex, age, and smoking. The concentrations of only 1 metabolite in unstimulated saliva, and of 3 metabolites stimulated saliva, showed significant correlation with salivary secretion volume, indicating that the salivary metabolomic profile and salivary secretion volume were independent factors. Masticatory stimulation affected not only salivary secretion volume, but also metabolite concentration patterns. A low correlation between the secretion volume and these patterns supports the conclusion that the salivary metabolomic profile may be a new indicator to characterize masticatory stimulation.

COnsortium of METabolomics Studies (COMETS)

Cancer.gov

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

Application of global metabolomic profiling of synovial fluid for osteoarthritis biomarkers.

PubMed

Carlson, Alyssa K; Rawle, Rachel A; Adams, Erik; Greenwood, Mark C; Bothner, Brian; June, Ronald K

2018-05-05

Osteoarthritis affects over 250 million individuals worldwide. Currently, there are no options for early diagnosis of osteoarthritis, demonstrating the need for biomarker discovery. To find biomarkers of osteoarthritis in human synovial fluid, we used high performance liquid-chromatography mass spectrometry for global metabolomic profiling. Metabolites were extracted from human osteoarthritic (n = 5), rheumatoid arthritic (n = 3), and healthy (n = 5) synovial fluid, and a total of 1233 metabolites were detected. Principal components analysis clearly distinguished the metabolomic profiles of diseased from healthy synovial fluid. Synovial fluid from rheumatoid arthritis patients contained expected metabolites consistent with the inflammatory nature of the disease. Similarly, unsupervised clustering analysis found that each disease state was associated with distinct metabolomic profiles and clusters of co-regulated metabolites. For osteoarthritis, co-regulated metabolites that were upregulated compared to healthy synovial fluid mapped to known disease processes including chondroitin sulfate degradation, arginine and proline metabolism, and nitric oxide metabolism. We utilized receiver operating characteristic analysis to determine the diagnostic value of each metabolite and identified 35 metabolites as potential biomarkers of osteoarthritis, with an area under the receiver operating characteristic curve >0.9. These metabolites included phosphatidylcholine, lysophosphatidylcholine, ceramides, myristate derivatives, and carnitine derivatives. This pilot study provides strong justification for a larger cohort-based study of human osteoarthritic synovial fluid using global metabolomics. The significance of these data is the demonstration that metabolomic profiling of synovial fluid can identify relevant biomarkers of joint disease. Copyright © 2018 Elsevier Inc. All rights reserved.

Genomic and Metabolomic Profile Associated to Microalbuminuria

PubMed Central

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

2014-01-01

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

A pharmaco-metabolomics approach in a clinical trial of ALS: Identification of predictive markers of progression.

PubMed

Blasco, Hélène; Patin, Franck; Descat, Amandine; Garçon, Guillaume; Corcia, Philippe; Gelé, Patrick; Lenglet, Timothée; Bede, Peter; Meininger, Vincent; Devos, David; Gossens, Jean François; Pradat, Pierre-François

2018-01-01

There is an urgent and unmet need for accurate biomarkers in Amyotrophic Lateral Sclerosis. A pharmaco-metabolomics study was conducted using plasma samples from the TRO19622 (olesoxime) trial to assess the link between early metabolomic profiles and clinical outcomes. Patients included in this trial were randomized into either Group O receiving olesoxime (n = 38) or Group P receiving placebo (n = 36). The metabolomic profile was assessed at time-point one (V1) and 12 months (V12) after the initiation of the treatment. High performance liquid chromatography coupled with tandem mass spectrometry was used to quantify 188 metabolites (Biocrates® commercial kit). Multivariate analysis based on machine learning approaches (i.e. Biosigner algorithm) was performed. Metabolomic profiles at V1 and V12 and changes in metabolomic profiles between V1 and V12 accurately discriminated between Groups O and P (p<5×10-6), and identified glycine, kynurenine and citrulline/arginine as the best predictors of group membership. Changes in metabolomic profiles were closely linked to clinical progression, and correlated with glutamine levels in Group P and amino acids, lipids and spermidine levels in Group O. Multivariate models accurately predicted disease progression and highlighted the discriminant role of sphingomyelins (SM C22:3, SM C24:1, SM OH C22:2, SM C16:1). To predict SVC from SM C24:1 in group O and SVC from SM OH C22:2 and SM C16:1 in group P+O, we noted a median sensitivity between 67% and 100%, a specificity between 66.7 and 71.4%, a positive predictive value between 66 and 75% and a negative predictive value between 70% and 100% in the test sets. This proof-of-concept study demonstrates that the metabolomics has a role in evaluating the biological effect of an investigational drug and may be a candidate biomarker as a secondary outcome measure in clinical trials.

High Aerobic Capacity Mitigates Changes in the Plasma Metabolomic Profile Associated with Aging.

PubMed

Falegan, Oluyemi S; Vogel, Hans J; Hittel, Dustin S; Koch, Lauren G; Britton, Steven L; Hepple, Russ T; Shearer, Jane

2017-02-03

Advancing age is associated with declines in maximal oxygen consumption. Declines in aerobic capacity not only contribute to the aging process but also are an independent risk factor for morbidity, cardiovascular disease, and all-cause mortality. Although statistically convincing, the relationships between aerobic capacity, aging, and disease risk remain largely unresolved. To this end, we employed sensitive, system-based metabolomics approach to determine whether enhanced aerobic capacity could mitigate some of the changes seen in the plasma metabolomic profile associated with aging. Metabolomic profiles of plasma samples obtained from young (13 month) and old (26 month) rats bred for low (LCR) or high (HCR) running capacity using proton nuclear magnetic resonance spectroscopy ( 1 H NMR) were examined. Results demonstrated strong profile separation in old and low aerobic capacity rats, whereas young and high aerobic capacity rat models were less predictive. Significantly differential metabolites between the groups include taurine, acetone, valine, and trimethylamine-N-oxide among other metabolites, specifically citrate, succinate, isovalerate, and proline, were differentially increased in older HCR animals compared with their younger counterparts. When interactions between age and aerobic capacity were examined, results demonstrated that enhanced aerobic capacity could mitigate some but not all age-associated alterations in the metabolomic profile.

Effect of masticatory stimulation on the quantity and quality of saliva and the salivary metabolomic profile

PubMed Central

Hoshi, Noriyuki; Soga, Tomoyoshi; Tomita, Masaru; Sugimoto, Masahiro; Kimoto, Katsuhiko

2017-01-01

Background This study characterized the changes in quality and quantity of saliva, and changes in the salivary metabolomic profile, to understand the effects of masticatory stimulation. Methods Stimulated and unstimulated saliva samples were collected from 55 subjects and salivary hydrophilic metabolites were comprehensively quantified using capillary electrophoresis-time-of-flight mass spectrometry. Results In total, 137 metabolites were identified and quantified. The concentrations of 44 metabolites in stimulated saliva were significantly higher than those in unstimulated saliva. Pathway analysis identified the upregulation of the urea cycle and synthesis and degradation pathways of glycine, serine, cysteine and threonine in stimulated saliva. A principal component analysis revealed that the effect of masticatory stimulation on salivary metabolomic profiles was less dependent on sample population sex, age, and smoking. The concentrations of only 1 metabolite in unstimulated saliva, and of 3 metabolites stimulated saliva, showed significant correlation with salivary secretion volume, indicating that the salivary metabolomic profile and salivary secretion volume were independent factors. Conclusions Masticatory stimulation affected not only salivary secretion volume, but also metabolite concentration patterns. A low correlation between the secretion volume and these patterns supports the conclusion that the salivary metabolomic profile may be a new indicator to characterize masticatory stimulation. PMID:28813487

First Trimester Urine and Serum Metabolomics for Prediction of Preeclampsia and Gestational Hypertension: A Prospective Screening Study.

PubMed

Austdal, Marie; Tangerås, Line H; Skråstad, Ragnhild B; Salvesen, Kjell; Austgulen, Rigmor; Iversen, Ann-Charlotte; Bathen, Tone F

2015-09-08

Hypertensive disorders of pregnancy, including preeclampsia, are major contributors to maternal morbidity. The goal of this study was to evaluate the potential of metabolomics to predict preeclampsia and gestational hypertension from urine and serum samples in early pregnancy, and elucidate the metabolic changes related to the diseases. Metabolic profiles were obtained by nuclear magnetic resonance spectroscopy of serum and urine samples from 599 women at medium to high risk of preeclampsia (nulliparous or previous preeclampsia/gestational hypertension). Preeclampsia developed in 26 (4.3%) and gestational hypertension in 21 (3.5%) women. Multivariate analyses of the metabolic profiles were performed to establish prediction models for the hypertensive disorders individually and combined. Urinary metabolomic profiles predicted preeclampsia and gestational hypertension at 51.3% and 40% sensitivity, respectively, at 10% false positive rate, with hippurate as the most important metabolite for the prediction. Serum metabolomic profiles predicted preeclampsia and gestational hypertension at 15% and 33% sensitivity, respectively, with increased lipid levels and an atherogenic lipid profile as most important for the prediction. Combining maternal characteristics with the urinary hippurate/creatinine level improved the prediction rates of preeclampsia in a logistic regression model. The study indicates a potential future role of clinical importance for metabolomic analysis of urine in prediction of preeclampsia.

Translating Metabolomics to Cardiovascular Biomarkers

PubMed Central

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

2012-01-01

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

Using MetaboAnalyst 3.0 for Comprehensive Metabolomics Data Analysis.

PubMed

Xia, Jianguo; Wishart, David S

2016-09-07

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

Effects of age, sex, and genotype on high-sensitivity metabolomic profiles in the fruit fly, Drosophila melanogaster

PubMed Central

Hoffman, Jessica M; Soltow, Quinlyn A; Li, Shuzhao; Sidik, Alfire; Jones, Dean P; Promislow, Daniel E L

2014-01-01

Researchers have used whole-genome sequencing and gene expression profiling to identify genes associated with age, in the hope of understanding the underlying mechanisms of senescence. But there is a substantial gap from variation in gene sequences and expression levels to variation in age or life expectancy. In an attempt to bridge this gap, here we describe the effects of age, sex, genotype, and their interactions on high-sensitivity metabolomic profiles in the fruit fly, Drosophila melanogaster. Among the 6800 features analyzed, we found that over one-quarter of all metabolites were significantly associated with age, sex, genotype, or their interactions, and multivariate analysis shows that individual metabolomic profiles are highly predictive of these traits. Using a metabolomic equivalent of gene set enrichment analysis, we identified numerous metabolic pathways that were enriched among metabolites associated with age, sex, and genotype, including pathways involving sugar and glycerophospholipid metabolism, neurotransmitters, amino acids, and the carnitine shuttle. Our results suggest that high-sensitivity metabolomic studies have excellent potential not only to reveal mechanisms that lead to senescence, but also to help us understand differences in patterns of aging among genotypes and between males and females. PMID:24636523

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

PubMed

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

2017-01-01

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

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

PubMed Central

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

2008-01-01

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

Fecal Microbiota and Metabolome in a Mouse Model of Spontaneous Chronic Colitis: Relevance to Human Inflammatory Bowel Disease.

PubMed

Robinson, Ainsley M; Gondalia, Shakuntla V; Karpe, Avinash V; Eri, Rajaraman; Beale, David J; Morrison, Paul D; Palombo, Enzo A; Nurgali, Kulmira

2016-12-01

Dysbiosis of the gut microbiota may be involved in the pathogenesis of inflammatory bowel disease (IBD). However, the mechanisms underlying the role of the intestinal microbiome and metabolome in IBD onset and its alteration during active treatment and recovery remain unknown. Animal models of chronic intestinal inflammation with similar microbial and metabolomic profiles would enable investigation of these mechanisms and development of more effective treatments. Recently, the Winnie mouse model of colitis closely representing the clinical symptoms and characteristics of human IBD has been developed. In this study, we have analyzed fecal microbial and metabolomic profiles in Winnie mice and discussed their relevance to human IBD. The 16S rRNA gene was sequenced from fecal DNA of Winnie and C57BL/6 mice to define operational taxonomic units at ≥97% similarity threshold. Metabolomic profiling of the same fecal samples was performed by gas chromatography-mass spectrometry. Composition of the dominant microbiota was disturbed, and prominent differences were evident at all levels of the intestinal microbiome in fecal samples from Winnie mice, similar to observations in patients with IBD. Metabolomic profiling revealed that chronic colitis in Winnie mice upregulated production of metabolites and altered several metabolic pathways, mostly affecting amino acid synthesis and breakdown of monosaccharides to short chain fatty acids. Significant dysbiosis in the Winnie mouse gut replicates many changes observed in patients with IBD. These results provide justification for the suitability of this model to investigate mechanisms underlying the role of intestinal microbiota and metabolome in the pathophysiology of IBD.

Autonomous Metabolomics for Rapid Metabolite Identification in Global Profiling

DOE PAGES

Benton, H. Paul; Ivanisevic, Julijana; Mahieu, Nathaniel G.; ...

2014-12-12

An autonomous metabolomic workflow combining mass spectrometry analysis with tandem mass spectrometry data acquisition was designed to allow for simultaneous data processing and metabolite characterization. Although previously tandem mass spectrometry data have been generated on the fly, the experiments described herein combine this technology with the bioinformatic resources of XCMS and METLIN. We can analyze large profiling datasets and simultaneously obtain structural identifications, as a result of this unique integration. Furthermore, validation of the workflow on bacterial samples allowed the profiling on the order of a thousand metabolite features with simultaneous tandem mass spectra data acquisition. The tandem mass spectrometrymore » data acquisition enabled automatic search and matching against the METLIN tandem mass spectrometry database, shortening the current workflow from days to hours. Overall, the autonomous approach to untargeted metabolomics provides an efficient means of metabolomic profiling, and will ultimately allow the more rapid integration of comparative analyses, metabolite identification, and data analysis at a systems biology level.« less

Deciphering the biological effects of acupuncture treatment modulating multiple metabolism pathways.

PubMed

Zhang, Aihua; Yan, Guangli; Sun, Hui; Cheng, Weiping; Meng, Xiangcai; Liu, Li; Xie, Ning; Wang, Xijun

2016-02-16

Acupuncture is an alternative therapy that is widely used to treat various diseases. However, detailed biological interpretation of the acupuncture stimulations is limited. We here used metabolomics and proteomics technology, thereby identifying the serum small molecular metabolites into the effect and mechanism pathways of standardized acupuncture treatments at 'Zusanli' acupoint which was the most often used acupoint in previous reports. Comprehensive overview of serum metabolic profiles during acupuncture stimulation was investigated. Thirty-four differential metabolites were identified in serum metabolome and associated with ten metabolism pathways. Importantly, we have found that high impact glycerophospholipid metabolism, fatty acid metabolism, ether lipid metabolism were acutely perturbed by acupuncture stimulation. As such, these alterations may be useful to clarify the biological mechanism of acupuncture stimulation. A series of differentially expressed proteins were identified and such effects of acupuncture stimulation were found to play a role in transport, enzymatic activity, signaling pathway or receptor interaction. Pathway analysis further revealed that most of these proteins were found to play a pivotal role in the regulation of multiple metabolism pathways. It demonstrated that the metabolomics coupled with proteomics as a powerful approach for potential applications in understanding the biological effects of acupuncture stimulation.

Pathway Activity Profiling (PAPi): from the metabolite profile to the metabolic pathway activity.

PubMed

Aggio, Raphael B M; Ruggiero, Katya; Villas-Bôas, Silas Granato

2010-12-01

Metabolomics is one of the most recent omics-technologies and uses robust analytical techniques to screen low molecular mass metabolites in biological samples. It has evolved very quickly during the last decade. However, metabolomics datasets are considered highly complex when used to relate metabolite levels to metabolic pathway activity. Despite recent developments in bioinformatics, which have improved the quality of metabolomics data, there is still no straightforward method capable of correlating metabolite level to the activity of different metabolic pathways operating within the cells. Thus, this kind of analysis still depends on extremely laborious and time-consuming processes. Here, we present a new algorithm Pathway Activity Profiling (PAPi) with which we are able to compare metabolic pathway activities from metabolite profiles. The applicability and potential of PAPi was demonstrated using a previously published data from the yeast Saccharomyces cerevisiae. PAPi was able to support the biological interpretations of the previously published observations and, in addition, generated new hypotheses in a straightforward manner. However, PAPi is time consuming to perform manually. Thus, we also present here a new R-software package (PAPi) which implements the PAPi algorithm and facilitates its usage to quickly compare metabolic pathways activities between different experimental conditions. Using the identified metabolites and their respective abundances as input, the PAPi package calculates pathways' Activity Scores, which represents the potential metabolic pathways activities and allows their comparison between conditions. PAPi also performs principal components analysis and analysis of variance or t-test to investigate differences in activity level between experimental conditions. In addition, PAPi generates comparative graphs highlighting up- and down-regulated pathway activity. These datasets are available in http://www.4shared.com/file/hTWyndYU/extra.html and http://www.4shared.com/file/VbQIIDeu/intra.html. PAPi package is available in: http://www.4shared.com/file/s0uIYWIg/PAPi_10.html s.villas-boas@auckland.ac.nz Supplementary data are available at Bioinformatics online.

Early Prediction of Lupus Nephritis Using Advanced Proteomics

DTIC Science & Technology

2011-06-01

spectroscopy-based metabolomic profiling , and apolipoprotein D, lipocalin-like prostaglandin D synthetase, hemopexin, ceruloplasmin, -1-B glycoprotein and...will be confirmed and enhanced using NMR- and MS-based metabonomics , by Dr. Michael Kennedy, Miami University. Changes in proteomic profiles will be...based metabolomic profiling , and apolipoprotein D, lipocalin-like prostaglandin D synthetase, hemopexin, ceruloplasmin, -1-B glycoprotein and

Nutrigenomics and metabolomics will change clinical nutrition and public health practice: insights from studies on dietary requirements for choline2

PubMed Central

Zeisel, Steven H

2008-01-01

Science is beginning to understand how genetic variation and epigenetic events alter requirements for, and responses to, nutrients (nutrigenomics). At the same time, methods for profiling almost all of the products of metabolism in a single sample of blood or urine are being developed (metabolomics). Relations between diet and nutrigenomic and metabolomic profiles and between those profiles and health have become important components of research that could change clinical practice in nutrition. Most nutrition studies assume that all persons have average dietary requirements, and the studies often do not plan for a large subset of subjects who differ in requirements for a nutrient. Large variances in responses that occur when such a population exists can result in statistical analyses that argue for a null effect. If nutrition studies could better identify responders and differentiate them from nonresponders on the basis of nutrigenomic or metabolomic profiles, the sensitivity to detect differences between groups could be greatly increased, and the resulting dietary recommendations could be appropriately targeted. It is not certain that nutrition will be the clinical specialty primarily responsible for nutrigenomics or metabolomics, because other disciplines currently dominate the development of portions of these fields. However, nutrition scientists' depth of understanding of human metabolism can be used to establish a role in the research and clinical programs that will arise from nutrigenomic and metabolomic profiling. Investments made today in training programs and in research methods could ensure a new foundation for clinical nutrition in the future. PMID:17823415

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

PubMed Central

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

2016-01-01

The gut microbiota is composed of a huge number of different bacteria, that produce a large amount of compounds playing a key role in microbe selection and in the construction of a metabolic signaling network. The microbial activities are affected by environmental stimuli leading to the generation of a wide number of compounds, that influence the host metabolome and human health. Indeed, metabolite profiles related to the gut microbiota can offer deep insights on the impact of lifestyle and dietary factors on chronic and acute diseases. Metagenomics, metaproteomics and metabolomics are some of the meta-omics approaches to study the modulation of the gut microbiota. Metabolomic research applied to biofluids allows to: define the metabolic profile; identify and quantify classes and compounds of interest; characterize small molecules produced by intestinal microbes; and define the biochemical pathways of metabolites. Mass spectrometry and nuclear magnetic resonance spectroscopy are the principal technologies applied to metabolomics in terms of coverage, sensitivity and quantification. Moreover, the use of biostatistics and mathematical approaches coupled with metabolomics play a key role in the extraction of biologically meaningful information from wide datasets. Metabolomic studies in gut microbiota-related research have increased, focusing on the generation of novel biomarkers, which could lead to the development of mechanistic hypotheses potentially applicable to the development of nutritional and personalized therapies. PMID:27507964

Metabolome analysis for discovering biomarkers of gastroenterological cancer.

PubMed

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

2014-09-01

Improvements in analytical technologies have made it possible to rapidly determine the concentrations of thousands of metabolites in any biological sample, which has resulted in metabolome analysis being applied to various types of research, such as clinical, cell biology, and plant/food science studies. The metabolome represents all of the end products and by-products of the numerous complex metabolic pathways operating in a biological system. Thus, metabolome analysis allows one to survey the global changes in an organism's metabolic profile and gain a holistic understanding of the changes that occur in organisms during various biological processes, e.g., during disease development. In clinical metabolomic studies, there is a strong possibility that differences in the metabolic profiles of human specimens reflect disease-specific states. Recently, metabolome analysis of biofluids, e.g., blood, urine, or saliva, has been increasingly used for biomarker discovery and disease diagnosis. Mass spectrometry-based techniques have been extensively used for metabolome analysis because they exhibit high selectivity and sensitivity during the identification and quantification of metabolites. Here, we describe metabolome analysis using liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry, and capillary electrophoresis-mass spectrometry. Furthermore, the findings of studies that attempted to discover biomarkers of gastroenterological cancer are also outlined. Finally, we discuss metabolome analysis-based disease diagnosis. Copyright © 2014 Elsevier B.V. All rights reserved.

A Decade of Genetic and Metabolomic Contributions to Type 2 Diabetes Risk Prediction

PubMed Central

Merino, Jordi; Leong, Aaron; Meigs, James B.

2018-01-01

Purpose of Review The purpose of this review was to summarize and reflect on advances over the past decade in human genetic and metabolomic discovery with particular focus on their contributions to type 2 diabetes (T2D) risk prediction. Recent Findings In the past 10 years, a combination of advances in genotyping efficiency, metabolomic profiling, bio-informatics approaches, and international collaboration have moved T2D genetics and metabolomics from a state of frustration to an abundance of new knowledge. Summary Efforts to control and prevent T2D have failed to stop this global epidemic. New approaches are needed, and although neither genetic nor metabolomic profiling yet have a clear clinical role, the rapid pace of accumulating knowledge offers the possibility for “multi-omic” prediction to improve health. PMID:29103096

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

PubMed

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

2017-07-04

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

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

EPA Science Inventory

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

Mathematical Modeling Approaches in Plant Metabolomics.

PubMed

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

2018-01-01

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

Conventional and Accelerated-Solvent Extractions of Green Tea (Camellia sinensis) for Metabolomics-based Chemometrics

PubMed Central

Kellogg, Joshua J.; Wallace, Emily D.; Graf, Tyler N.; Oberlies, Nicholas H.; Cech, Nadja B.

2018-01-01

Metabolomics has emerged as an important analytical technique for multiple applications. The value of information obtained from metabolomics analysis depends on the degree to which the entire metabolome is present and the reliability of sample treatment to ensure reproducibility across the study. The purpose of this study was to compare methods of preparing complex botanical extract samples prior to metabolomics profiling. Two extraction methodologies, accelerated solvent extraction and a conventional solvent maceration, were compared using commercial green tea [Camellia sinensis (L.) Kuntze (Theaceae)] products as a test case. The accelerated solvent protocol was first evaluated to ascertain critical factors influencing extraction using a D-optimal experimental design study. The accelerated solvent and conventional extraction methods yielded similar metabolite profiles for the green tea samples studied. The accelerated solvent extraction yielded higher total amounts of extracted catechins, was more reproducible, and required less active bench time to prepare the samples. This study demonstrates the effectiveness of accelerated solvent as an efficient methodology for metabolomics studies. PMID:28787673

Genomic and Metabolomic Profile Associated to Clustering of Cardio-Metabolic Risk Factors

PubMed Central

Marrachelli, Vannina G.; Rentero, Pilar; Mansego, María L.; Morales, Jose Manuel; Galan, Inma; Pardo-Tendero, Mercedes; Martinez, Fernando; Martin-Escudero, Juan Carlos; Briongos, Laisa; Chaves, Felipe Javier; Redon, Josep; Monleon, Daniel

2016-01-01

Background To identify metabolomic and genomic markers associated with the presence of clustering of cardiometabolic risk factors (CMRFs) from a general population. Methods and Findings One thousand five hundred and two subjects, Caucasian, > 18 years, representative of the general population, were included. Blood pressure measurement, anthropometric parameters and metabolic markers were measured. Subjects were grouped according the number of CMRFs (Group 1: <2; Group 2: 2; Group 3: 3 or more CMRFs). Using SNPlex, 1251 SNPs potentially associated to clustering of three or more CMRFs were analyzed. Serum metabolomic profile was assessed by 1H NMR spectra using a Brucker Advance DRX 600 spectrometer. From the total population, 1217 (mean age 54±19, 50.6% men) with high genotyping call rate were analysed. A differential metabolomic profile, which included products from mitochondrial metabolism, extra mitochondrial metabolism, branched amino acids and fatty acid signals were observed among the three groups. The comparison of metabolomic patterns between subjects of Groups 1 to 3 for each of the genotypes associated to those subjects with three or more CMRFs revealed two SNPs, the rs174577_AA of FADS2 gene and the rs3803_TT of GATA2 transcription factor gene, with minimal or no statistically significant differences. Subjects with and without three or more CMRFs who shared the same genotype and metabolomic profile differed in the pattern of CMRFS cluster. Subjects of Group 3 and the AA genotype of the rs174577 had a lower prevalence of hypertension compared to the CC and CT genotype. In contrast, subjects of Group 3 and the TT genotype of the rs3803 polymorphism had a lower prevalence of T2DM, although they were predominantly males and had higher values of plasma creatinine. Conclusions The results of the present study add information to the metabolomics profile and to the potential impact of genetic factors on the variants of clustering of cardiometabolic risk factors. PMID:27589269

Genomic and Metabolomic Profile Associated to Clustering of Cardio-Metabolic Risk Factors.

PubMed

Marrachelli, Vannina G; Rentero, Pilar; Mansego, María L; Morales, Jose Manuel; Galan, Inma; Pardo-Tendero, Mercedes; Martinez, Fernando; Martin-Escudero, Juan Carlos; Briongos, Laisa; Chaves, Felipe Javier; Redon, Josep; Monleon, Daniel

2016-01-01

To identify metabolomic and genomic markers associated with the presence of clustering of cardiometabolic risk factors (CMRFs) from a general population. One thousand five hundred and two subjects, Caucasian, > 18 years, representative of the general population, were included. Blood pressure measurement, anthropometric parameters and metabolic markers were measured. Subjects were grouped according the number of CMRFs (Group 1: <2; Group 2: 2; Group 3: 3 or more CMRFs). Using SNPlex, 1251 SNPs potentially associated to clustering of three or more CMRFs were analyzed. Serum metabolomic profile was assessed by 1H NMR spectra using a Brucker Advance DRX 600 spectrometer. From the total population, 1217 (mean age 54±19, 50.6% men) with high genotyping call rate were analysed. A differential metabolomic profile, which included products from mitochondrial metabolism, extra mitochondrial metabolism, branched amino acids and fatty acid signals were observed among the three groups. The comparison of metabolomic patterns between subjects of Groups 1 to 3 for each of the genotypes associated to those subjects with three or more CMRFs revealed two SNPs, the rs174577_AA of FADS2 gene and the rs3803_TT of GATA2 transcription factor gene, with minimal or no statistically significant differences. Subjects with and without three or more CMRFs who shared the same genotype and metabolomic profile differed in the pattern of CMRFS cluster. Subjects of Group 3 and the AA genotype of the rs174577 had a lower prevalence of hypertension compared to the CC and CT genotype. In contrast, subjects of Group 3 and the TT genotype of the rs3803 polymorphism had a lower prevalence of T2DM, although they were predominantly males and had higher values of plasma creatinine. The results of the present study add information to the metabolomics profile and to the potential impact of genetic factors on the variants of clustering of cardiometabolic risk factors.

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

PubMed

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

2015-01-01

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

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

PubMed

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

2018-02-01

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

Untargeted mass spectrometry-based metabolomic profiling of pleural effusions: fatty acids as novel cancer biomarkers for malignant pleural effusions.

PubMed

Lam, Ching-Wan; Law, Chun-Yiu

2014-09-05

Untargeted mass spectrometry-based metabolomic profiling is a powerful analytical method used for broad-spectrum identification and quantification of metabolites in biofluids in human health and disease states. In this study, we exploit metabolomic profiling for cancer biomarker discovery for diagnosis of malignant pleural effusions. We envisage the result will be clinically useful since currently there are no cancer biomarkers that are accurate enough for the diagnosis of malignant pleural effusions. Metabolomes of 32 malignant pleural effusions from lung cancer patients and 18 benign effusions from patients with pulmonary tuberculosis were analyzed using reversed-phase liquid chromatography tandem mass spectrometry (LC-MS/MS) using AB SCIEX TripleTOF 5600. MS spectra were analyzed using XCMS, PeakView, and LipidView. Metabolome-Wide Association Study (MWAS) was performed by Receiver Operating Characteristic Curve Explorer and Tester (ROCCET). Insignificant markers were filtered out using a metabolome-wide significance level (MWSL) with p-value < 2 × 10(-5) for t test. Only compounds in Human Metabolome Database (HMDB) will be used as cancer biomarkers. ROCCET analysis of ESI positive and negative MS spectra revealed free fatty acid (FFA) 18:1 (oleic acid) had the largest area-under-ROC of 0.96 (95% CI = 0.87-1.00) in malignant pleural effusions. Using a ratio of FFA 18:1-to-ceramide (d18:1/16:0), the area-under-ROC was further increased to 0.99 (95% CI = 0.91-1.00) with sensitivity 93.8% and specificity 100.0%. Using untargeted metabolomic profiling, the diagnostic cancer biomarker with the largest area-under-ROC can be determined objectively. This lipogenic phenotype could be explained by overexpression of fatty acid synthase (FASN) in cancer cells. The diagnostic performance of FFA 18:1-to-ceramide (d18:1/16:0) ratio supports its use for diagnosis of malignant pleural effusions.

Metabolomics for secondary metabolite research.

PubMed

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

2013-11-11

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

Development of an Integrated Metabolomic Profiling Approach for Infectious Diseases Research

PubMed Central

Lv, Haitao; Hung, Chia S.; Chaturvedi, Kaveri S.; Hooton, Thomas M.; Henderson, Jeffrey P.

2013-01-01

Metabolomic profiling offers direct insights into the chemical environment and metabolic pathway activities at sites of human disease. During infection, this environment may receive important contributions from both host and pathogen. Here we apply untargeted metabolomics approach to identify compounds associated with an E. coli urinary tract infection population. Correlative and structural data from minimally processed samples were obtained using an optimized LC-MS platform capable of resolving ∼2300 molecular features. Principal components analysis readily distinguished patient groups and multiple supervised chemometric analyses resolved robust metabolomic shifts between groups. These analyses revealed nine compounds whose provisional structures suggest candidate infection-associated endocrine, catabolic, and lipid pathways. Several of these metabolite signatures may derive from microbial processing of host metabolites. Overall, this study highlights the ability of metabolomic approaches to directly identify compounds encountered by, and produced from, bacterial pathogens within human hosts. PMID:21922104

Application of Fourier-transform ion cyclotron resonance mass spectrometry to metabolic profiling and metabolite identification.

PubMed

Ohta, Daisaku; Kanaya, Shigehiko; Suzuki, Hideyuki

2010-02-01

Metabolomics, as an essential part of genomics studies, intends holistic understanding of metabolic networks through simultaneous analysis of a myriad of both known and unknown metabolites occurring in living organisms. The initial stage of metabolomics was designed for the reproducible analyses of known metabolites based on their comparison to available authentic compounds. Such metabolomics platforms were mostly based on mass spectrometry (MS) technologies enabled by a combination of different ionization methods together with a variety of separation steps including LC, GC, and CE. Among these, Fourier-transform ion cyclotron resonance MS (FT-ICR/MS) is distinguished from other MS technologies by its ultrahigh resolution power in mass to charge ratio (m/z). The potential of FT-ICR/MS as a distinctive metabolomics tool has been demonstrated in nontargeted metabolic profiling and functional characterization of novel genes. Here, we discuss both the advantages and difficulties encountered in the FT-ICR/MS metabolomics studies.

Biomarker analysis of American toad (Anaxyrus americanus) and grey tree frog (Hyla versicolor) tadpoles following exposure to atrazine.

PubMed

Snyder, Marcía N; Henderson, W Matthew; Glinski, Donna A; Purucker, S Thomas

2017-01-01

The objective of the current study was to use a biomarker-based approach to investigate the influence of atrazine exposure on American toad (Anaxyrus americanus) and grey tree frog (Hyla versicolor) tadpoles. Atrazine is one of the most frequently detected herbicides in environmental matrices throughout the United States. In surface waters, it has been found at concentrations from 0.04-2859μg/L and thus presents a likely exposure scenario for non-target species such as amphibians. Studies have examined the effect of atrazine on the metamorphic parameters of amphibians, however, the data are often contradictory. Gosner stage 22-24 tadpoles were exposed to 0 (control), 10, 50, 250 or 1250μg/L of atrazine for 48h. Endogenous polar metabolites were extracted and analyzed using gas chromatography coupled with mass spectrometry. Statistical analyses of the acquired spectra with machine learning classification models demonstrated identifiable changes in the metabolomic profiles between exposed and control tadpoles. Support vector machine models with recursive feature elimination created a more efficient, non-parametric data analysis and increased interpretability of metabolomic profiles. Biochemical fluxes observed in the exposed groups of both A. americanus and H. versicolor displayed perturbations in a number of classes of biological macromolecules including fatty acids, amino acids, purine nucleosides, pyrimidines, and mono- and di-saccharides. Metabolomic pathway analyses are consistent with findings of other studies demonstrating disruption of amino acid and energy metabolism from atrazine exposure to non-target species. Copyright © 2016. Published by Elsevier B.V.

Proteome and metabolome profiling of cytokinin action in Arabidopsis identifying both distinct and similar responses to cytokinin down- and up-regulation.

PubMed

Černý, Martin; Kuklová, Alena; Hoehenwarter, Wolfgang; Fragner, Lena; Novák, Ondrej; Rotková, Gabriela; Jedelsky, Petr L; Žáková, Katerina; Šmehilová, Mária; Strnad, Miroslav; Weckwerth, Wolfram; Brzobohaty, Bretislav

2013-11-01

In plants, numerous developmental processes are controlled by cytokinin (CK) levels and their ratios to levels of other hormones. While molecular mechanisms underlying the regulatory roles of CKs have been intensely researched, proteomic and metabolomic responses to CK deficiency are unknown. Transgenic Arabidopsis seedlings carrying inducible barley cytokinin oxidase/dehydrogenase (CaMV35S>GR>HvCKX2) and agrobacterial isopentenyl transferase (CaMV35S>GR>ipt) constructs were profiled to elucidate proteome- and metabolome-wide responses to down- and up-regulation of CK levels, respectively. Proteome profiling identified >1100 proteins, 155 of which responded to HvCKX2 and/or ipt activation, mostly involved in growth, development, and/or hormone and light signalling. The metabolome profiling covered 79 metabolites, 33 of which responded to HvCKX2 and/or ipt activation, mostly amino acids, carbohydrates, and organic acids. Comparison of the data sets obtained from activated CaMV35S>GR>HvCKX2 and CaMV35S>GR>ipt plants revealed unexpectedly extensive overlaps. Integration of the proteomic and metabolomic data sets revealed: (i) novel components of molecular circuits involved in CK action (e.g. ribosomal proteins); (ii) previously unrecognized links to redox regulation and stress hormone signalling networks; and (iii) CK content markers. The striking overlaps in profiles observed in CK-deficient and CK-overproducing seedlings might explain surprising previously reported similarities between plants with down- and up-regulated CK levels.

Atmospheric vs. anaerobic processing of metabolome samples for the metabolite profiling of a strict anaerobic bacterium, Clostridium acetobutylicum.

PubMed

Lee, Sang-Hyun; Kim, Sooah; Kwon, Min-A; Jung, Young Hoon; Shin, Yong-An; Kim, Kyoung Heon

2014-12-01

Well-established metabolome sample preparation is a prerequisite for reliable metabolomic data. For metabolome sampling of a Gram-positive strict anaerobe, Clostridium acetobutylicum, fast filtration and metabolite extraction with acetonitrile/methanol/water (2:2:1, v/v) at -20°C under anaerobic conditions has been commonly used. This anaerobic metabolite processing method is laborious and time-consuming since it is conducted in an anaerobic chamber. Also, there have not been any systematic method evaluation and development of metabolome sample preparation for strict anaerobes and Gram-positive bacteria. In this study, metabolome sampling and extraction methods were rigorously evaluated and optimized for C. acetobutylicum by using gas chromatography/time-of-flight mass spectrometry-based metabolomics, in which a total of 116 metabolites were identified. When comparing the atmospheric (i.e., in air) and anaerobic (i.e., in an anaerobic chamber) processing of metabolome sample preparation, there was no significant difference in the quality and quantity of the metabolomic data. For metabolite extraction, pure methanol at -20°C was a better solvent than acetonitrile/methanol/water (2:2:1, v/v/v) at -20°C that is frequently used for C. acetobutylicum, and metabolite profiles were significantly different depending on extraction solvents. This is the first evaluation of metabolite sample preparation under aerobic processing conditions for an anaerobe. This method could be applied conveniently, efficiently, and reliably to metabolome analysis for strict anaerobes in air. © 2014 Wiley Periodicals, Inc.

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

PubMed

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

2017-10-01

Bronchiolitis is the most common lower respiratory infection in infants; however, it remains unclear which infants with bronchiolitis will develop severe illness. In addition, although emerging evidence indicates associations of the upper-airway microbiome with bronchiolitis severity, little is known about the mechanisms linking airway microbes and host response to disease severity. To determine the relations among the nasopharyngeal airway metabolome profiles, microbiome profiles, and severity in infants with bronchiolitis. We conducted a multicenter prospective cohort study of infants (age <1 yr) hospitalized with bronchiolitis. By applying metabolomic and metagenomic (16S ribosomal RNA gene and whole-genome shotgun sequencing) approaches to 144 nasopharyngeal airway samples collected within 24 hours of hospitalization, we determined metabolome and microbiome profiles and their association with higher severity, defined by the use of positive pressure ventilation (i.e., continuous positive airway pressure and/or intubation). Nasopharyngeal airway metabolome profiles significantly differed by bronchiolitis severity (P < 0.001). Among 254 metabolites identified, a panel of 25 metabolites showed high sensitivity (84%) and specificity (86%) in predicting the use of positive pressure ventilation. The intensity of these metabolites was correlated with relative abundance of Streptococcus pneumoniae. In the pathway analysis, sphingolipid metabolism was the most significantly enriched subpathway in infants with positive pressure ventilation use compared with those without (P < 0.001). Enrichment of sphingolipid metabolites was positively correlated with the relative abundance of S. pneumoniae. Although further validation is needed, our multiomic analyses demonstrate the potential of metabolomics to predict bronchiolitis severity and better understand microbe-host interaction.

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

PubMed

Zha, Haihong; Cai, Yuping; Yin, Yandong; Wang, Zhuozhong; Li, Kang; Zhu, Zheng-Jiang

2018-03-20

The complexity of metabolome presents a great analytical challenge for quantitative metabolite profiling, and restricts the application of metabolomics in biomarker discovery. Targeted metabolomics using multiple-reaction monitoring (MRM) technique has excellent capability for quantitative analysis, but suffers from the limited metabolite coverage. To address this challenge, we developed a new strategy, namely, SWATHtoMRM, which utilizes the broad coverage of SWATH-MS technology to develop high-coverage targeted metabolomics method. Specifically, SWATH-MS technique was first utilized to untargeted profile one pooled biological sample and to acquire the MS 2 spectra for all metabolites. Then, SWATHtoMRM was used to extract the large-scale MRM transitions for targeted analysis with coverage as high as 1000-2000 metabolites. Then, we demonstrated the advantages of SWATHtoMRM method in quantitative analysis such as coverage, reproducibility, sensitivity, and dynamic range. Finally, we applied our SWATHtoMRM approach to discover potential metabolite biomarkers for colorectal cancer (CRC) diagnosis. A high-coverage targeted metabolomics method with 1303 metabolites in one injection was developed to profile colorectal cancer tissues from CRC patients. A total of 20 potential metabolite biomarkers were discovered and validated for CRC diagnosis. In plasma samples from CRC patients, 17 out of 20 potential biomarkers were further validated to be associated with tumor resection, which may have a great potential in assessing the prognosis of CRC patients after tumor resection. Together, the SWATHtoMRM strategy provides a new way to develop high-coverage targeted metabolomics method, and facilitates the application of targeted metabolomics in disease biomarker discovery. The SWATHtoMRM program is freely available on the Internet ( http://www.zhulab.cn/software.php ).

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

PubMed

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

2014-07-01

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

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

PubMed

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

2017-05-15

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

Metabolome Profiling of Partial and Fully Reprogrammed Induced Pluripotent Stem Cells.

PubMed

Park, Soon-Jung; Lee, Sang A; Prasain, Nutan; Bae, Daekyeong; Kang, Hyunsu; Ha, Taewon; Kim, Jong Soo; Hong, Ki-Sung; Mantel, Charlie; Moon, Sung-Hwan; Broxmeyer, Hal E; Lee, Man Ryul

2017-05-15

Acquisition of proper metabolomic fate is required to convert somatic cells toward fully reprogrammed pluripotent stem cells. The majority of induced pluripotent stem cells (iPSCs) are partially reprogrammed and have a transcriptome different from that of the pluripotent stem cells. The metabolomic profile and mitochondrial metabolic functions required to achieve full reprogramming of somatic cells to iPSC status have not yet been elucidated. Clarification of the metabolites underlying reprogramming mechanisms should enable further optimization to enhance the efficiency of obtaining fully reprogrammed iPSCs. In this study, we characterized the metabolites of human fully reprogrammed iPSCs, partially reprogrammed iPSCs, and embryonic stem cells (ESCs). Using capillary electrophoresis time-of-flight mass spectrometry-based metabolomics, we found that 89% of analyzed metabolites were similarly expressed in fully reprogrammed iPSCs and human ESCs (hESCs), whereas partially reprogrammed iPSCs shared only 74% similarly expressed metabolites with hESCs. Metabolomic profiling analysis suggested that converting mitochondrial respiration to glycolytic flux is critical for reprogramming of somatic cells into fully reprogrammed iPSCs. This characterization of metabolic reprogramming in iPSCs may enable the development of new reprogramming parameters for enhancing the generation of fully reprogrammed human iPSCs.

Real-time metabolome profiling of the metabolic switch between starvation and growth.

PubMed

Link, Hannes; Fuhrer, Tobias; Gerosa, Luca; Zamboni, Nicola; Sauer, Uwe

2015-11-01

Metabolic systems are often the first networks to respond to environmental changes, and the ability to monitor metabolite dynamics is key for understanding these cellular responses. Because monitoring metabolome changes is experimentally tedious and demanding, dynamic data on time scales from seconds to hours are scarce. Here we describe real-time metabolome profiling by direct injection of living bacteria, yeast or mammalian cells into a high-resolution mass spectrometer, which enables automated monitoring of about 300 compounds in 15-30-s cycles over several hours. We observed accumulation of energetically costly biomass metabolites in Escherichia coli in carbon starvation-induced stationary phase, as well as the rapid use of these metabolites upon growth resumption. By combining real-time metabolome profiling with modeling and inhibitor experiments, we obtained evidence for switch-like feedback inhibition in amino acid biosynthesis and for control of substrate availability through the preferential use of the metabolically cheaper one-step salvaging pathway over costly ten-step de novo purine biosynthesis during growth resumption.

Conventional and accelerated-solvent extractions of green tea (camellia sinensis) for metabolomics-based chemometrics.

PubMed

Kellogg, Joshua J; Wallace, Emily D; Graf, Tyler N; Oberlies, Nicholas H; Cech, Nadja B

2017-10-25

Metabolomics has emerged as an important analytical technique for multiple applications. The value of information obtained from metabolomics analysis depends on the degree to which the entire metabolome is present and the reliability of sample treatment to ensure reproducibility across the study. The purpose of this study was to compare methods of preparing complex botanical extract samples prior to metabolomics profiling. Two extraction methodologies, accelerated solvent extraction and a conventional solvent maceration, were compared using commercial green tea [Camellia sinensis (L.) Kuntze (Theaceae)] products as a test case. The accelerated solvent protocol was first evaluated to ascertain critical factors influencing extraction using a D-optimal experimental design study. The accelerated solvent and conventional extraction methods yielded similar metabolite profiles for the green tea samples studied. The accelerated solvent extraction yielded higher total amounts of extracted catechins, was more reproducible, and required less active bench time to prepare the samples. This study demonstrates the effectiveness of accelerated solvent as an efficient methodology for metabolomics studies. Copyright © 2017. Published by Elsevier B.V.

Metabolomic Profiles Delineate Signature Metabolic Shifts during Estrogen Deficiency-Induced Bone Loss in Rat by GC-TOF/MS

PubMed Central

Zhang, Qi; Ying, Hanjie; A, Jiye; Sun, Jianguo; Wu, Di; Wang, Yonglu; Li, Jing; Liu, Yinhui

2013-01-01

Postmenopausal osteoporosis is a complicated and multi-factorial disease. To study the metabolic profiles and pathways activated in osteoporosis, Eight rats were oophorectomized (OVX group) to represent postmenopausal osteoporosis and the other eight rats were sham operated (Sham group) to be the control. The biochemical changes were assessed with metabolomics using a gas chromatography/time-of-flight mass spectrometry. Metabolomic profile using serial blood samples obtained prior to and at different time intervals after OVX were analyzed by principal component analysis (PCA) and Partial least squares-discriminant analysis (PLS-DA). The conventional indicators (bone mineral density, serum Bone alkaline phosphatase (B-ALP) and N-telopeptide of type I collagen (NTx) of osteoporosis in rats were also determined simultaneously. In OVX group, the metabolomics method could describe the endogenous changes of the disease more sensitively and systematically than the conventional criteria during the progression of osteoporosis. Significant metabolomic difference was also observed between the OVX and Sham groups. The metabolomic analyses of rat plasma showed that levels of arachidonic acid, octadecadienoic acid, branched-chain amino acids (valine, leucine and isoleucine), homocysteine, hydroxyproline and ketone bodies (3-Hydroxybutyric Acid) significantly elevated, while levels of docosahexaenoic acid, dodecanoic acid and lysine significantly decreased in OVX group compared with those in the homeochronous Sham group. Considering such metabolites are closely related to the pathology of the postmenopausal osteoporosis, the results suggest that potential biomarkers for the early diagnosis or the pathogenesis of osteoporosis might be identified via metabolomic study. PMID:23408954

Long-term fertilization determines different metabolomic profiles and responses in saplings of three rainforest tree species with different adult canopy position.

PubMed

Gargallo-Garriga, Albert; Wright, S Joseph; Sardans, Jordi; Pérez-Trujillo, Míriam; Oravec, Michal; Večeřová, Kristýna; Urban, Otmar; Fernández-Martínez, Marcos; Parella, Teodor; Peñuelas, Josep

2017-01-01

Tropical rainforests are frequently limited by soil nutrient availability. However, the response of the metabolic phenotypic plasticity of trees to an increase of soil nutrient availabilities is poorly understood. We expected that increases in the ability of a nutrient that limits some plant processes should be detected by corresponding changes in plant metabolome profile related to such processes. We studied the foliar metabolome of saplings of three abundant tree species in a 15 year field NPK fertilization experiment in a Panamanian rainforest. The largest differences were among species and explained 75% of overall metabolome variation. The saplings of the large canopy species, Tetragastris panamensis, had the lowest concentrations of all identified amino acids and the highest concentrations of most identified secondary compounds. The saplings of the "mid canopy" species, Alseis blackiana, had the highest concentrations of amino acids coming from the biosynthesis pathways of glycerate-3P, oxaloacetate and α-ketoglutarate, and the saplings of the low canopy species, Heisteria concinna, had the highest concentrations of amino acids coming from the pyruvate synthesis pathways. The changes in metabolome provided strong evidence that different nutrients limit different species in different ways. With increasing P availability, the two canopy species shifted their metabolome towards larger investment in protection mechanisms, whereas with increasing N availability, the sub-canopy species increased its primary metabolism. The results highlighted the proportional distinct use of different nutrients by different species and the resulting different metabolome profiles in this high diversity community are consistent with the ecological niche theory.

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

PubMed

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

2017-12-01

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

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

PubMed

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

2015-01-20

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

Menthol smokers: metabolomic profiling and smoking behavior

PubMed Central

Hsu, Ping-Ching; Lan, Renny S.; Brasky, Theodore M.; Marian, Catalin; Cheema, Amrita K.; Ressom, Habtom W.; Loffredo, Christopher A.; Pickworth, Wallace B.; Shields, Peter G.

2016-01-01

Background The use of menthol in cigarettes and marketing is under consideration for regulation by the FDA. However, the effects of menthol on smoking behavior and carcinogen exposure have been inconclusive. We previously reported metabolomic profiling for cigarette smokers, and novelly identified a menthol-glucuronide (MG) as the most significant metabolite directly related to smoking. Here, MG is studied in relation to smoking behavior and metabolomic profiles. Methods A cross-sectional study of 105 smokers who smoked two cigarettes in the laboratory one hour apart. Blood nicotine, MG and exhaled carbon monoxide (CO) boosts were determined (the difference before and after smoking). Spearman's correlation, Chi-Square and ANCOVA adjusted for gender, race and cotinine levels for menthol smokers assessed the relationship of MG boost, smoking behavior, and metabolic profiles. Multivariate metabolite characterization using supervised Partial Least Squares-Discriminant Analysis (PLS-DA) was carried out for the classification of metabolomics profiles. Results MG boost was positively correlated with CO boost, nicotine boost, average puff volume, puff duration, and total smoke exposure. Classification using PLS-DA, MG was the top metabolite discriminating metabolome of menthol vs. non-menthol smokers. Among menthol smokers, forty-two metabolites were significantly correlated with MG boost, which linked to cellular functions such as of cell death, survival, and movement. Conclusion Plasma MG boost is a new smoking behavior biomarker that may provides novel information over self-reported use of menthol cigarettes by integrating different smoking measures for understanding smoking behavior and harm of menthol cigarettes. Impacts These results provide insight into the biological effect of menthol smoking. PMID:27628308

Nutrigenomics in human intervention studies: current status, lessons learned and future perspectives.

PubMed

Wittwer, Jonas; Rubio-Aliaga, Isabel; Hoeft, Birgit; Bendik, Igor; Weber, Peter; Daniel, Hannelore

2011-03-01

Nutrigenomics applications comprise transcript-, proteome- and metabolome-profiling techniques in which responses to diets or individual ingredients are assessed in biological samples. They may also include the characterization of heterogeneity in relevant genes that affect the biological processes. This review explores various areas of nutrition and food sciences in which transcriptome-, proteome- and metabolome-analyses have been applied in human intervention studies, including nutrigenetics aspects and discusses the advantages and limitations of the methodologies. Despite the power of the profiling techniques to generate huge data sets, a critical assessment of the study outcomes emphasizes the current constraints in data interpretation, including huge knowledge gaps, the need for improved study designs and more comprehensive phenotyping of volunteers before selection for study participation. In this respect, nutrigenomics faces the same problems as all other areas of the life sciences, employing the same tools. However, there is a growing trend toward systemic approaches in which different technologies are combined and applied to the same sample, allowing physiological changes to be assessed more robustly throughout all molecular layers of mRNA, protein and metabolite changes. Nutrigenomics is thereby maturing as a branch of the life sciences and is gaining significant recognition in the scientific community. Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

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

PubMed

Gielisch, Ina; Meierhofer, David

2015-01-02

Complex I (CI; NADH dehydrogenase) deficiency causes mitochondrial diseases, including Leigh syndrome. A variety of clinical symptoms of CI deficiency are known, including neurodegeneration. Here, we report an integrative study combining liquid chromatography-mass spectrometry (LC-MS)-based metabolome and proteome profiling in CI deficient HeLa cells. We report a rapid LC-MS-based method for the relative quantification of targeted metabolome profiling with an additional layer of confidence by applying multiple reaction monitoring (MRM) ion ratios for further identity confirmation and robustness. The proteome was analyzed by label-free quantification (LFQ). More than 6000 protein groups were identified. Pathway and network analyses revealed that the respiratory chain was highly deregulated, with metabolites such as FMN, FAD, NAD(+), and ADP, direct players of the OXPHOS system, and metabolites of the TCA cycle decreased up to 100-fold. Synthesis of functional iron-sulfur clusters, which are of central importance for the electron transfer chain, and degradation products like bilirubin were also significantly reduced. Glutathione metabolism on the pathway level, as well as individual metabolite components such as NADPH, glutathione (GSH), and oxidized glutathione (GSSG), was downregulated. Overall, metabolome and proteome profiles in CI deficient cells correlated well, supporting our integrated approach.

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

PubMed

Le Moyec, Laurence; Robert, Céline; Triba, Mohamed N; Billat, Véronique L; Mata, Xavier; Schibler, Laurent; Barrey, Eric

2014-01-01

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.

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

PubMed

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

2014-01-01

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

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

PubMed Central

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

2013-01-01

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

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

PubMed

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

2016-01-01

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

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

PubMed Central

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

2016-01-01

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

Metabolomic Modularity Analysis (MMA) to Quantify Human Liver Perfusion Dynamics.

PubMed

Sridharan, Gautham Vivek; Bruinsma, Bote Gosse; Bale, Shyam Sundhar; Swaminathan, Anandh; Saeidi, Nima; Yarmush, Martin L; Uygun, Korkut

2017-11-13

Large-scale -omics data are now ubiquitously utilized to capture and interpret global responses to perturbations in biological systems, such as the impact of disease states on cells, tissues, and whole organs. Metabolomics data, in particular, are difficult to interpret for providing physiological insight because predefined biochemical pathways used for analysis are inherently biased and fail to capture more complex network interactions that span multiple canonical pathways. In this study, we introduce a nov-el approach coined Metabolomic Modularity Analysis (MMA) as a graph-based algorithm to systematically identify metabolic modules of reactions enriched with metabolites flagged to be statistically significant. A defining feature of the algorithm is its ability to determine modularity that highlights interactions between reactions mediated by the production and consumption of cofactors and other hub metabolites. As a case study, we evaluated the metabolic dynamics of discarded human livers using time-course metabolomics data and MMA to identify modules that explain the observed physiological changes leading to liver recovery during subnormothermic machine perfusion (SNMP). MMA was performed on a large scale liver-specific human metabolic network that was weighted based on metabolomics data and identified cofactor-mediated modules that would not have been discovered by traditional metabolic pathway analyses.

Metabolic profiles are principally different between cancers of the liver, pancreas and breast.

PubMed

Budhu, Anuradha; Terunuma, Atsushi; Zhang, Geng; Hussain, S Perwez; Ambs, Stefan; Wang, Xin Wei

2014-01-01

Molecular profiling of primary tumors may facilitate the classification of patients with cancer into more homogenous biological groups to aid clinical management. Metabolomic profiling has been shown to be a powerful tool in characterizing the biological mechanisms underlying a disease but has not been evaluated for its ability to classify cancers by their tissue of origin. Thus, we assessed metabolomic profiling as a novel tool for multiclass cancer characterization. Global metabolic profiling was employed to identify metabolites in paired tumor and non-tumor liver (n=60), breast (n=130) and pancreatic (n=76) tissue specimens. Unsupervised principal component analysis showed that metabolites are principally unique to each tissue and cancer type. Such a difference can also be observed even among early stage cancers, suggesting a significant and unique alteration of global metabolic pathways associated with each cancer type. Our global high-throughput metabolomic profiling study shows that specific biochemical alterations distinguish liver, pancreatic and breast cancer and could be applied as cancer classification tools to differentiate tumors based on tissue of origin.

Metabolomics: beyond biomarkers and towards mechanisms

PubMed Central

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

2017-01-01

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

Differential expression profiling of serum proteins and metabolites for biomarker discovery

NASA Astrophysics Data System (ADS)

Roy, Sushmita Mimi; Anderle, Markus; Lin, Hua; Becker, Christopher H.

2004-11-01

A liquid chromatography-mass spectrometry (LC-MS) proteomics and metabolomics platform is presented for quantitative differential expression analysis. Proteome profiles obtained from 1.5 [mu]L of human serum show ~5000 de-isotoped and quantifiable molecular ions. Approximately 1500 metabolites are observed from 100 [mu]L of serum. Quantification is based on reproducible sample preparation and linear signal intensity as a function of concentration. The platform is validated using human serum, but is generally applicable to all biological fluids and tissues. The median coefficient of variation (CV) for ~5000 proteomic and ~1500 metabolomic molecular ions is approximately 25%. For the case of C-reactive protein, results agree with quantification by immunoassay. The independent contributions of two sources of variance, namely sample preparation and LC-MS analysis, are respectively quantified as 20.4 and 15.1% for the proteome, and 19.5 and 13.5% for the metabolome, for median CV values. Furthermore, biological diversity for ~20 healthy individuals is estimated by measuring the variance of ~6500 proteomic and metabolomic molecular ions in sera for each sample; the median CV is 22.3% for the proteome and 16.7% for the metabolome. Finally, quantitative differential expression profiling is applied to a clinical study comparing healthy individuals and rheumatoid arthritis (RA) patients.

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

PubMed

Zhen, Shoumin; Dong, Kun; Deng, Xiong; Zhou, Jiaxing; Xu, Xuexin; Han, Caixia; Zhang, Wenying; Xu, Yanhao; Wang, Zhimin; Yan, Yueming

2016-08-01

Metabolites in wheat grains greatly influence nutritional values. Wheat provides proteins, minerals, B-group vitamins and dietary fiber to humans. These metabolites are important to human health. However, the metabolome of the grain during the development of bread wheat has not been studied so far. In this work the first dynamic metabolome of the developing grain of the elite Chinese bread wheat cultivar Zhongmai 175 was analyzed, using non-targeted gas chromatography/mass spectrometry (GC/MS) for metabolite profiling. In total, 74 metabolites were identified over the grain developmental stages. Metabolite-metabolite correlation analysis revealed that the metabolism of amino acids, carbohydrates, organic acids, amines and lipids was interrelated. An integrated metabolic map revealed a distinct regulatory profile. The results provide information that can be used by metabolic engineers and molecular breeders to improve wheat grain quality. The present metabolome approach identified dynamic changes in metabolite levels, and correlations among such levels, in developing seeds. The comprehensive metabolic map may be useful when breeding programs seek to improve grain quality. The work highlights the utility of GC/MS-based metabolomics, in conjunction with univariate and multivariate data analysis, when it is sought to understand metabolic changes in developing seeds. © 2015 Society of Chemical Industry. © 2015 Society of Chemical Industry.

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

Noecker, Cecilia; Eng, Alexander; Srinivasan, Sujatha

ABSTRACT Multiple molecular assays now enable high-throughput profiling of the ecology, metabolic capacity, and activity of the human microbiome. However, to date, analyses of such multi-omic data typically focus on statistical associations, often ignoring extensive prior knowledge of the mechanisms linking these various facets of the microbiome. Here, we introduce a comprehensive framework to systematically link variation in metabolomic data with community composition by utilizing taxonomic, genomic, and metabolic information. Specifically, we integrate available and inferred genomic data, metabolic network modeling, and a method for predicting community-wide metabolite turnover to estimate the biosynthetic and degradation potential of a given community.more » Our framework then compares variation in predicted metabolic potential with variation in measured metabolites’ abundances to evaluate whether community composition can explain observed shifts in the community metabolome, and to identify key taxa and genes contributing to the shifts. Focusing on two independent vaginal microbiome data sets, each pairing 16S community profiling with large-scale metabolomics, we demonstrate that our framework successfully recapitulates observed variation in 37% of metabolites. Well-predicted metabolite variation tends to result from disease-associated metabolism. We further identify several disease-enriched species that contribute significantly to these predictions. Interestingly, our analysis also detects metabolites for which the predicted variation negatively correlates with the measured variation, suggesting environmental control points of community metabolism. Applying this framework to gut microbiome data sets reveals similar trends, including prediction of bile acid metabolite shifts. This framework is an important first step toward a system-level multi-omic integration and an improved mechanistic understanding of the microbiome activity and dynamics in health and disease. IMPORTANCEStudies characterizing both the taxonomic composition and metabolic profile of various microbial communities are becoming increasingly common, yet new computational methods are needed to integrate and interpret these data in terms of known biological mechanisms. Here, we introduce an analytical framework to link species composition and metabolite measurements, using a simple model to predict the effects of community ecology on metabolite concentrations and evaluating whether these predictions agree with measured metabolomic profiles. We find that a surprisingly large proportion of metabolite variation in the vaginal microbiome can be predicted based on species composition (including dramatic shifts associated with disease), identify putative mechanisms underlying these predictions, and evaluate the roles of individual bacterial species and genes. Analysis of gut microbiome data using this framework recovers similar community metabolic trends. This framework lays the foundation for model-based multi-omic integrative studies, ultimately improving our understanding of microbial community metabolism.« less

USING PHARMACOKINETIC DATA TO INTERPRET METABOLOMIC CHANGES IN CD-1 MICE TREATED WITH TRIAZOLE FUNGICIDES

EPA Science Inventory

Triazoles are a class of fungicides widely used in both pharmaceutical and agricultural applications. These compounds elicit a variety of toxic effects including disruption of normal metabolic processes such as steroidogenesis. Metabolomics is used to measure dynamic changes in e...

Tools for the functional interpretation of metabolomic experiments.

PubMed

Chagoyen, Monica; Pazos, Florencio

2013-11-01

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

Long-term fertilization determines different metabolomic profiles and responses in saplings of three rainforest tree species with different adult canopy position

PubMed Central

Gargallo-Garriga, Albert; Wright, S. Joseph; Sardans, Jordi; Pérez-Trujillo, Míriam; Oravec, Michal; Večeřová, Kristýna; Urban, Otmar; Fernández-Martínez, Marcos; Parella, Teodor; Peñuelas, Josep

2017-01-01

Background Tropical rainforests are frequently limited by soil nutrient availability. However, the response of the metabolic phenotypic plasticity of trees to an increase of soil nutrient availabilities is poorly understood. We expected that increases in the ability of a nutrient that limits some plant processes should be detected by corresponding changes in plant metabolome profile related to such processes. Methodology/Principal findings We studied the foliar metabolome of saplings of three abundant tree species in a 15 year field NPK fertilization experiment in a Panamanian rainforest. The largest differences were among species and explained 75% of overall metabolome variation. The saplings of the large canopy species, Tetragastris panamensis, had the lowest concentrations of all identified amino acids and the highest concentrations of most identified secondary compounds. The saplings of the “mid canopy” species, Alseis blackiana, had the highest concentrations of amino acids coming from the biosynthesis pathways of glycerate-3P, oxaloacetate and α-ketoglutarate, and the saplings of the low canopy species, Heisteria concinna, had the highest concentrations of amino acids coming from the pyruvate synthesis pathways. Conclusions/Significance The changes in metabolome provided strong evidence that different nutrients limit different species in different ways. With increasing P availability, the two canopy species shifted their metabolome towards larger investment in protection mechanisms, whereas with increasing N availability, the sub-canopy species increased its primary metabolism. The results highlighted the proportional distinct use of different nutrients by different species and the resulting different metabolome profiles in this high diversity community are consistent with the ecological niche theory. PMID:28493911

Metabolomic analysis of the selection response of Drosophila melanogaster to environmental stress: are there links to gene expression and phenotypic traits?

NASA Astrophysics Data System (ADS)

Malmendal, Anders; Sørensen, Jesper Givskov; Overgaard, Johannes; Holmstrup, Martin; Nielsen, Niels Chr.; Loeschcke, Volker

2013-05-01

We investigated the global metabolite response to artificial selection for tolerance to stressful conditions such as cold, heat, starvation, and desiccation, and for longevity in Drosophila melanogaster. Our findings were compared to data from other levels of biological organization, including gene expression, physiological traits, and organismal stress tolerance phenotype. Overall, we found that selection for environmental stress tolerance changes the metabolomic 1H NMR fingerprint largely in a similar manner independent of the trait selected for, indicating that experimental evolution led to a general stress selection response at the metabolomic level. Integrative analyses across data sets showed little similarity when general correlations between selection effects at the level of the metabolome and gene expression were compared. This is likely due to the fact that the changes caused by these selection regimes were rather mild and/or that the dominating determinants for gene expression and metabolite levels were different. However, expression of a number of genes was correlated with the metabolite data. Many of the identified genes were general stress response genes that are down-regulated in response to selection for some of the stresses in this study. Overall, the results illustrate that selection markedly alters the metabolite profile and that the coupling between different levels of biological organization indeed is present though not very strong for stress selection at this level. The results highlight the extreme complexity of environmental stress adaptation and the difficulty of extrapolating and interpreting responses across levels of biological organization.

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

PubMed Central

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

2017-01-01

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

Metabolomics: A Primer.

PubMed

Liu, Xiaojing; Locasale, Jason W

2017-04-01

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

Transcriptomic and metabolomic profiles of Chinese citrus fly, Bactrocera minax (Diptera: Tephritidae), along with pupal development provide insight into diapause program

PubMed Central

Fan, Huan; Xiong, Ke-Cai; Liu, Ying-Hong

2017-01-01

The Chinese citrus fly, Bactrocera minax (Enderlein), is a devastating citrus pest in Asia. This univoltine insect enters obligatory pupal diapause in each generation, while little is known about the course and the molecular mechanisms of diapause. In this study, the course of diapause was determined by measuring the respiratory rate throughout the pupal stage. In addition, the variation of transcriptomic and metabolomic profiles of pupae at five developmental stages (pre-, early-, middle-, late-, and post-diapause) were evaluated by next-generation sequencing technology and 1H nuclear magnetic resonance spectroscopy (NMR), respectively. A total of 4,808 genes were significantly altered in ten pairwise comparisons, representing major shifts in metabolism and signal transduction as well as endocrine system and digestive system. Gene expression profiles were validated by qRT-PCR analysis. In addition, 48 metabolites were identified and quantified by 1H NMR. Nine of which significantly contributed to the variation in the metabolomic profiles, especially proline and trehalose. Moreover, the samples collected within diapause maintenance (early-, middle-, and late-diapause) only exhibited marginal transcriptomic and metabolomic variation with each other. These findings greatly improve our understanding of B. minax diapause and lay the foundation for further pertinent studies. PMID:28704500

A metabolomics-based method for studying the effect of yfcC gene in Escherichia coli on metabolism.

PubMed

Wang, Xiyue; Xie, Yuping; Gao, Peng; Zhang, Sufang; Tan, Haidong; Yang, Fengxu; Lian, Rongwei; Tian, Jing; Xu, Guowang

2014-04-15

Metabolomics is a potent tool to assist in identifying the function of unknown genes through analysis of metabolite changes in the context of varied genetic backgrounds. However, the availability of a universal unbiased profiling analysis is still a big challenge. In this study, we report an optimized metabolic profiling method based on gas chromatography-mass spectrometry for Escherichia coli. It was found that physiological saline at -80°C could ensure satisfied metabolic quenching with less metabolite leakage. A solution of methanol/water (21:79, v/v) was proved to be efficient for intracellular metabolite extraction. This method was applied to investigate the metabolome difference among wild-type E. coli, its yfcC deletion, and overexpression mutants. Statistical and bioinformatic analysis of the metabolic profiling data indicated that the expression of yfcC potentially affected the metabolism of glyoxylate shunt. This finding was further validated by real-time quantitative polymerase chain reactions showing that expression of aceA and aceB, the key genes in glyoxylate shunt, was upregulated by yfcC. This study exemplifies the robustness of the proposed metabolic profiling analysis strategy and its potential roles in investigating unknown gene functions in view of metabolome difference. Copyright © 2014 Elsevier Inc. All rights reserved.

Targeted metabolomic profiling in rat tissues reveals sex differences.

PubMed

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

2018-03-16

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

Nutritional metabolomics: Progress in addressing complexity in diet and health

PubMed Central

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

2013-01-01

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

Metabolomic analysis of amino acid and energy metabolism in rats supplemented with chlorogenic acid

PubMed Central

Ruan, Zheng; Yang, Yuhui; Zhou, Yan; Wen, Yanmei; Ding, Sheng; Liu, Gang; Wu, Xin; Deng, Zeyuan; Assaad, Houssein; Wu, Guoyao

2016-01-01

This study was conducted to investigate effects of chlorogenic acid (CGA) supplementation on serum and hepatic metabolomes in rats. Rats received daily intragastric administration of either CGA (60 mg/kg body weight) or distilled water (control) for 4 weeks. Growth performance, serum biochemical profiles, and hepatic morphology were measured. Additionally, serum and liver tissue extracts were analyzed for metabolomes by high-resolution 1H nuclear magnetic resonance-based metabolomics and multivariate statistics. CGA did not affect rat growth performance, serum biochemical profiles, or hepatic morphology. However, supplementation with CGA decreased serum concentrations of lactate, pyruvate, succinate, citrate, β-hydroxybutyrate and acetoacetate, while increasing serum concentrations of glycine and hepatic concentrations of glutathione. These results suggest that CGA supplementation results in perturbation of energy and amino acid metabolism in rats. We suggest that glycine and glutathione in serum may be useful biomarkers for biological properties of CGA on nitrogen metabolism in vivo. PMID:24927697

Metabolomics in Newborns.

PubMed

Noto, Antonio; Fanos, Vassilios; Dessì, Angelica

2016-01-01

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

The Importance of Experimental Design, Quality Assurance, and Control in Plant Metabolomics Experiments.

PubMed

Martins, Marina C M; Caldana, Camila; Wolf, Lucia Daniela; de Abreu, Luis Guilherme Furlan

2018-01-01

The output of metabolomics relies to a great extent upon the methods and instrumentation to identify, quantify, and access spatial information on as many metabolites as possible. However, the most modern machines and sophisticated tools for data analysis cannot compensate for inappropriate harvesting and/or sample preparation procedures that modify metabolic composition and can lead to erroneous interpretation of results. In addition, plant metabolism has a remarkable degree of complexity, and the number of identified compounds easily surpasses the number of samples in metabolomics analyses, increasing false discovery risk. These aspects pose a large challenge when carrying out plant metabolomics experiments. In this chapter, we address the importance of a proper experimental design taking into consideration preventable complications and unavoidable factors to achieve success in metabolomics analysis. We also focus on quality control and standardized procedures during the metabolomics workflow.

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

PubMed

Tsugawa, Hiroshi

2018-01-29

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

Metabolomics through the lens of precision cardiovascular medicine.

PubMed

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

2017-03-20

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

Integrative Analysis of Longitudinal Metabolomics Data from a Personal Multi-Omics Profile

PubMed Central

Stanberry, Larissa; Mias, George I.; Haynes, Winston; Higdon, Roger; Snyder, Michael; Kolker, Eugene

2013-01-01

The integrative personal omics profile (iPOP) is a pioneering study that combines genomics, transcriptomics, proteomics, metabolomics and autoantibody profiles from a single individual over a 14-month period. The observation period includes two episodes of viral infection: a human rhinovirus and a respiratory syncytial virus. The profile studies give an informative snapshot into the biological functioning of an organism. We hypothesize that pathway expression levels are associated with disease status. To test this hypothesis, we use biological pathways to integrate metabolomics and proteomics iPOP data. The approach computes the pathways’ differential expression levels at each time point, while taking into account the pathway structure and the longitudinal design. The resulting pathway levels show strong association with the disease status. Further, we identify temporal patterns in metabolite expression levels. The changes in metabolite expression levels also appear to be consistent with the disease status. The results of the integrative analysis suggest that changes in biological pathways may be used to predict and monitor the disease. The iPOP experimental design, data acquisition and analysis issues are discussed within the broader context of personal profiling. PMID:24958148

CE-MS for metabolomics: Developments and applications in the period 2014-2016.

PubMed

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

2017-01-01

CE-MS can be considered a useful analytical technique for the global profiling of (highly) polar and charged metabolites in various samples. Over the past few years, significant advancements have been made in CE-MS approaches for metabolomics studies. In this paper, which is a follow-up of a previous review paper covering the years 2012-2014 (Electrophoresis 2015, 36, 212-224), recent CE-MS strategies developed for metabolomics covering the literature from July 2014 to June 2016 are outlined. Attention will be paid to new CE-MS approaches for the profiling of anionic metabolites and the potential of SPE coupled to CE-MS is also demonstrated. Representative examples illustrate the applicability of CE-MS in the fields of biomedical, clinical, microbial, plant, and food metabolomics. A complete overview of recent CE-MS-based metabolomics studies is given in a table, which provides information on sample type and pretreatment, capillary coatings, and MS detection mode. Finally, general conclusions and perspectives are given. © 2016 The Authors ELECTROPHORESIS Published by Wiley-VCH Verlag GmbH & Co. KGaA.

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

PubMed

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

2014-01-01

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

Metabolomic Change Precedes Apple Superficial Scald Symptoms

USDA-ARS?s Scientific Manuscript database

Metabolic profiling of 621 metabolites was employed to characterize metabolomic changes associated with ‘Granny Smith’ apple superficial scald development following 1-MCP or DPA treatment. Partial least squares-discriminant analyses were used to link metabolites with scald, postharvest treatments, ...

Transglycosylated Starch Improves Insulin Response and Alters Lipid and Amino Acid Metabolome in a Growing Pig Model

PubMed Central

Newman, Monica A.; Zebeli, Qendrim; Eberspächer, Eva; Grüll, Dietmar; Molnar, Timea; Metzler-Zebeli, Barbara U.

2017-01-01

Due to the functional properties and physiological effects often associated with chemically modified starches, significant interest lies in their development for incorporation in processed foods. This study investigated the effect of transglycosylated cornstarch (TGS) on blood glucose, insulin, and serum metabolome in the pre- and postprandial phase in growing pigs. Eight jugular vein-catheterized barrows were fed two diets containing 72% purified starch (waxy cornstarch (CON) or TGS). A meal tolerance test (MTT) was performed with serial blood sampling for glucose, insulin, lipids, and metabolome profiling. TGS-fed pigs had reduced postprandial insulin (p < 0.05) and glucose (p < 0.10) peaks compared to CON-fed pigs. The MTT showed increased (p < 0.05) serum urea with TGS-fed pigs compared to CON, indicative of increased protein catabolism. Metabolome profiling showed reduced (p < 0.05) amino acids such as alanine and glutamine with TGS, suggesting increased gluconeogenesis compared to CON, probably due to a reduction in available glucose. Of all metabolites affected by dietary treatment, alkyl-acyl-phosphatidylcholines and sphingomyelins were generally increased (p < 0.05) preprandially, whereas diacyl-phosphatidylcholines and lysophosphatidylcholines were decreased (p < 0.05) postprandially in TGS-fed pigs compared to CON. In conclusion, TGS led to changes in postprandial insulin and glucose metabolism, which may have caused the alterations in serum amino acid and phospholipid metabolome profiles. PMID:28300770

Transglycosylated Starch Improves Insulin Response and Alters Lipid and Amino Acid Metabolome in a Growing Pig Model.

PubMed

Newman, Monica A; Zebeli, Qendrim; Eberspächer, Eva; Grüll, Dietmar; Molnar, Timea; Metzler-Zebeli, Barbara U

2017-03-16

Due to the functional properties and physiological effects often associated with chemically modified starches, significant interest lies in their development for incorporation in processed foods. This study investigated the effect of transglycosylated cornstarch (TGS) on blood glucose, insulin, and serum metabolome in the pre- and postprandial phase in growing pigs. Eight jugular vein-catheterized barrows were fed two diets containing 72% purified starch (waxy cornstarch (CON) or TGS). A meal tolerance test (MTT) was performed with serial blood sampling for glucose, insulin, lipids, and metabolome profiling. TGS-fed pigs had reduced postprandial insulin ( p < 0.05) and glucose ( p < 0.10) peaks compared to CON-fed pigs. The MTT showed increased ( p < 0.05) serum urea with TGS-fed pigs compared to CON, indicative of increased protein catabolism. Metabolome profiling showed reduced ( p < 0.05) amino acids such as alanine and glutamine with TGS, suggesting increased gluconeogenesis compared to CON, probably due to a reduction in available glucose. Of all metabolites affected by dietary treatment, alkyl-acyl-phosphatidylcholines and sphingomyelins were generally increased ( p < 0.05) preprandially, whereas diacyl-phosphatidylcholines and lysophosphatidylcholines were decreased ( p < 0.05) postprandially in TGS-fed pigs compared to CON. In conclusion, TGS led to changes in postprandial insulin and glucose metabolism, which may have caused the alterations in serum amino acid and phospholipid metabolome profiles.

Untargeted Metabolomics Strategies—Challenges and Emerging Directions

NASA Astrophysics Data System (ADS)

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

2016-12-01

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

Plasma metabolomic profiles predict near-term death among individuals with lower extremity peripheral arterial disease.

PubMed

Huang, Chiang-Ching; McDermott, Mary M; Liu, Kiang; Kuo, Ching-Hua; Wang, San-Yuan; Tao, Huimin; Tseng, Yufeng Jane

2013-10-01

Individuals with peripheral arterial disease (PAD) have a nearly two-fold increased risk of all-cause and cardiovascular disease mortality compared to those without PAD. This pilot study determined whether metabolomic profiling can accurately identify patients with PAD who are at increased risk of near-term mortality. We completed a case-control study using (1)H NMR metabolomic profiling of plasma from 20 decedents with PAD, without critical limb ischemia, who had blood drawn within 8 months prior to death (index blood draw) and within 10 to 28 months prior to death (preindex blood draw). Twenty-one PAD participants who survived more than 30 months after their index blood draw served as a control population. Results showed distinct metabolomic patterns between preindex decedent, index decedent, and survivor samples. The major chemical signals contributing to the differential pattern (between survivors and decedents) arose from the fatty acyl chain protons of lipoproteins and the choline head group protons of phospholipids. Using the top 40 chemical signals for which the intensity was most distinct between survivor and preindex decedent samples, classification models predicted near-term all-cause death with overall accuracy of 78% (32/41), a sensitivity of 85% (17/20), and a specificity of 71% (15/21). When comparing survivor with index decedent samples, the overall classification accuracy was optimal at 83% (34/41) with a sensitivity of 80% (16/20) and a specificity of 86% (18/21), using as few as the top 10 to 20 chemical signals. Our results suggest that metabolomic profiling of plasma may be useful for identifying PAD patients at increased risk for near-term death. Larger studies using more sensitive metabolomic techniques are needed to identify specific metabolic pathways associated with increased risk of near-term all-cause mortality among PAD patients. Copyright © 2013 Society for Vascular Surgery. Published by Mosby, Inc. All rights reserved.

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

PubMed

Metzler-Zebeli, Barbara U; Eberspächer, Eva; Grüll, Dietmar; Kowalczyk, Lidia; Molnar, Timea; Zebeli, Qendrim

2015-01-01

Developing host digestion-resistant starches to promote human health is of great research interest. Chemically modified starches (CMS) are widely used in processed foods and although the modification of the starch molecule allows specific reduction in digestibility, the metabolic effects of CMS have been less well described. This short-term study evaluated the impact of enzymatically modified starch (EMS) on fasting and postprandial profiles of blood glucose, insulin and lipids, and serum metabolome in growing pigs. Eight jugular-vein catheterized pigs (initial body weight, 37.4 kg; 4 months of age) were fed 2 diets containing 72% purified starch (EMS or waxy corn starch (control)) in a cross-over design for 7 days. On day 8, an 8-hour meal tolerance test (MTT) was performed with serial blood samplings. Besides biochemical analysis, serum was analysed for 201 metabolites through targeted mass spectrometry-based metabolomic approaches. Pigs fed the EMS diet showed increased (P<0.05) immediate serum insulin and plasma glucose response compared to pigs fed the control diet; however, area-under-the-curves for insulin and glucose were not different among diets. Results from MTT indicated reduced postprandial serum triglycerides with EMS versus control diet (P<0.05). Likewise, serum metabolome profiling identified characteristic changes in glycerophospholipid, lysophospholipids, sphingomyelins and amino acid metabolome profiles with EMS diet compared to control diet. Results showed rapid adaptations of blood metabolites to dietary starch shifts within 7 days. In conclusion, EMS ingestion showed potential to attenuate postprandial raise in serum lipids and suggested constant alteration in the synthesis or breakdown of sphingolipids and phospholipids which might be a health benefit of EMS consumption. Because serum insulin was not lowered, more research is warranted to reveal possible underlying mechanisms behind the observed changes in the profile of serum lipid metabolome in response to EMS consumption.

Metabolomics-Driven Nutraceutical Evaluation of Diverse Green Tea Cultivars

PubMed Central

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. Conclusions/Significance Our findings suggest that metabolic profiling is a useful approach for nutraceutical evaluation of the health promotion effects of diverse tea cultivars. This may propose a novel strategy for functional food design. PMID:21853132

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

PubMed Central

Metzler-Zebeli, Barbara U.; Eberspächer, Eva; Grüll, Dietmar; Kowalczyk, Lidia; Molnar, Timea; Zebeli, Qendrim

2015-01-01

Developing host digestion-resistant starches to promote human health is of great research interest. Chemically modified starches (CMS) are widely used in processed foods and although the modification of the starch molecule allows specific reduction in digestibility, the metabolic effects of CMS have been less well described. This short-term study evaluated the impact of enzymatically modified starch (EMS) on fasting and postprandial profiles of blood glucose, insulin and lipids, and serum metabolome in growing pigs. Eight jugular-vein catheterized pigs (initial body weight, 37.4 kg; 4 months of age) were fed 2 diets containing 72% purified starch (EMS or waxy corn starch (control)) in a cross-over design for 7 days. On day 8, an 8-hour meal tolerance test (MTT) was performed with serial blood samplings. Besides biochemical analysis, serum was analysed for 201 metabolites through targeted mass spectrometry-based metabolomic approaches. Pigs fed the EMS diet showed increased (P<0.05) immediate serum insulin and plasma glucose response compared to pigs fed the control diet; however, area-under-the-curves for insulin and glucose were not different among diets. Results from MTT indicated reduced postprandial serum triglycerides with EMS versus control diet (P<0.05). Likewise, serum metabolome profiling identified characteristic changes in glycerophospholipid, lysophospholipids, sphingomyelins and amino acid metabolome profiles with EMS diet compared to control diet. Results showed rapid adaptations of blood metabolites to dietary starch shifts within 7 days. In conclusion, EMS ingestion showed potential to attenuate postprandial raise in serum lipids and suggested constant alteration in the synthesis or breakdown of sphingolipids and phospholipids which might be a health benefit of EMS consumption. Because serum insulin was not lowered, more research is warranted to reveal possible underlying mechanisms behind the observed changes in the profile of serum lipid metabolome in response to EMS consumption. PMID:26076487

Global metabolomic profiling targeting childhood obesity in the Hispanic population

USDA-ARS?s Scientific Manuscript database

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

METABOLOMICS FOR DEVELOPING MARKERS OF CHEMICAL EXPOSURE AND DISTINGUISHING TOXICITY PATHWAYS

EPA Science Inventory

Metabolomics involves the application of advanced analytical and statistical tools to profile changes in levels of endogenous metabolites in tissues and biofluids resulting from disease onset, stress, or chemical exposure. Nuclear Magnetic Resonance (NMR) spectroscopy-based meta...

METABOLOMICS AS A DIAGNOSTIC TOOL FOR SMALL FISH TOXICOLOGY RESEARCH

EPA Science Inventory

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

Combined methionine deprivation and chloroethylnitrosourea have time-dependent therapeutic synergy on melanoma tumors that NMR spectroscopy-based metabolomics explains by methionine and phospholipid metabolism reprogramming.

PubMed

Guénin, Samuel; Morvan, Daniel; Thivat, Emilie; Stepien, Georges; Demidem, Aicha

2009-01-01

Methionine (Met) deprivation stress (MDS) is proposed in association with chemotherapy in the treatment of some cancers. A synergistic effect of this combination is generally acknowledged. However, little is known on the mechanism of the response to this therapeutic strategy. A model of B16 melanoma tumor in vivo was treated by MDS alone and in combination with chloroethylnitrosourea (CENU). It was applied recent developments in proton-NMR spectroscopy-based metabolomics for providing information on the metabolic response of tumors to MDS and combination with chemotherapy. MDS inhibited tumor growth during the deprivation period and growth resumption thereafter. The combination of MDS with CENU induced an effective time-dependent synergy on growth inhibition. Metabolite profiling during MDS showed a decreased Met content (P < 0.01) despite the preservation of the protein content, disorders in sulfur-containing amino acids, glutamine/proline, and phospholipid metabolism [increase of glycerophosphorylcholine (P < 0.01), decrease in phosphocholine (P < 0.05)]. The metabolic profile of MDS combined with CENU and ANOVA analysis revealed the implication of Met and phospholipid metabolism in the observed synergy, which may be interpreted as a Met-sparing metabolic reprogramming of tumors. It follows that combination therapy of MDS with CENU seems to intensify adaptive processes, which may set limitations to this therapeutic strategy.

A proposed metabolic strategy for monitoring disease progression in Alzheimer's disease.

PubMed

Greenberg, Nicola; Grassano, Antonio; Thambisetty, Madhav; Lovestone, Simon; Legido-Quigley, Cristina

2009-04-01

A specific, sensitive and essentially non-invasive assay to diagnose and monitor Alzheimer's disease (AD) would be valuable to both clinicians and medical researchers. The aim of this study was to perform a metabonomic statistical analysis on plasma fingerprints. Objectives were to investigate novel biomarkers indicative of AD, to consider the role of bile acids as AD biomarkers and to consider whether mild cognitive impairment (MCI) is a separate disease from AD. Samples were analysed by ultraperformance liquid chromatography-MS and resulting data sets were interpreted using soft-independent modelling of class analogy statistical analysis methods. PCA models did not show any grouping of subjects by disease state. Partial least-squares discriminant analysis (PLS-DS) models yielded class separation for AD. However, as with earlier studies, model validation revealed a predictive power of Q(2)<0.5 and indicating their unsuitability for predicting disease state. Three bile acids were extracted from the data and quantified, up-regulation was observed for MCI and AD patients. PLS-DA did not support MCI being considered as a separate disease from AD with MCI patient metabolic profiles being significantly closer to AD patients than controls. This study suggested that further investigation into the lipid fraction of the metabolome may yield useful biomarkers for AD and metabolomic profiles could be used to predict disease state in a clinical setting.

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

PubMed Central

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

2017-01-01

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

Effects of Histidine Supplementation on Global Serum and Urine 1H NMR-based Metabolomics and Serum Amino Acid Profiles in Obese Women from a Randomized Controlled Study.

PubMed

Du, Shanshan; Sun, Shuhong; Liu, Liyan; Zhang, Qiao; Guo, Fuchuan; Li, Chunlong; Feng, Rennan; Sun, Changhao

2017-06-02

The aim of current study was to investigate the metabolic changes associated with histidine supplementation in serum and urine metabolic signatures and serum amino acid (AA) profiles. Serum and urine 1 H NMR-based metabolomics and serum AA profiles were employed in 32 and 37 obese women with metabolic syndrome (MetS) intervened with placebo or histidine for 12 weeks. Multivariable statistical analysis were conducted to define characteristic metabolites. In serum 1 H NMR metabolic profiles, increases in histidine, glutamine, aspartate, glycine, choline, and trimethylamine-N-oxide (TMAO) were observed; meanwhile, decreases in cholesterol, triglycerides, fatty acids and unsaturated lipids, acetone, and α/β-glucose were exhibited after histidine supplement. In urine 1 H NMR metabolic profiles, citrate, creatinine/creatine, methylguanidine, and betaine + TMAO were higher, while hippurate was lower in histidine supplement group. In serum AA profiles, 10 AAs changed after histidine supplementation, including increased histidine, glycine, alanine, lysine, asparagine, and tyrosine and decreased leucine, isoleucine, ornithine, and citrulline. The study showed a systemic metabolic response in serum and urine metabolomics and AA profiles to histidine supplementation, showing significantly changed metabolism in AAs, lipid, and glucose in obese women with MetS.

Comprehensive Plasma Metabolomic Analyses of Atherosclerotic Progression Reveal Alterations in Glycerophospholipid and Sphingolipid Metabolism in Apolipoprotein E-deficient Mice

PubMed Central

Dang, Vi T.; Huang, Aric; Zhong, Lexy H.; Shi, Yuanyuan; Werstuck, Geoff H.

2016-01-01

Atherosclerosis is the major underlying cause of most cardiovascular diseases. Despite recent advances, the molecular mechanisms underlying the pathophysiology of atherogenesis are not clear. In this study, comprehensive plasma metabolomics were used to investigate early-stage atherosclerotic development and progression in chow-fed apolipoprotein E-deficient mice at 5, 10 and 15 weeks of age. Comprehensive plasma metabolomic profiles, based on 4365 detected metabolite features, differentiate atherosclerosis-prone from atherosclerosis-resistant models. Metabolites in the sphingomyelin pathway were significantly altered prior to detectable lesion formation and at all subsequent time-points. The cytidine diphosphate-diacylglycerol pathway was up-regulated during stage I of atherosclerosis, while metabolites in the phosphatidylethanolamine and glycosphingolipid pathways were augmented in mice with stage II lesions. These pathways, involving glycerophospholipid and sphingolipid metabolism, were also significantly affected during the course of atherosclerotic progression. Our findings suggest that distinct plasma metabolomic profiles can differentiate the different stages of atherosclerotic progression. This study reveals that alteration of specific, previously unreported pathways of glycerophospholipid and sphingolipid metabolism are associated with atherosclerosis. The clear difference in the level of several metabolites supports the use of plasma lipid profiling as a diagnostic tool of atherogenesis. PMID:27721472

Plasma metabolomic profiles of breast cancer patients after short-term limonene intervention.

PubMed

Miller, Jessica A; Pappan, Kirk; Thompson, Patricia A; Want, Elizabeth J; Siskos, Alexandros P; Keun, Hector C; Wulff, Jacob; Hu, Chengcheng; Lang, Julie E; Chow, H-H Sherry

2015-01-01

Limonene is a lipophilic monoterpene found in high levels in citrus peel. Limonene demonstrates anticancer properties in preclinical models with effects on multiple cellular targets at varying potency. While of interest as a cancer chemopreventive, the biologic activity of limonene in humans is poorly understood. We conducted metabolite profiling in 39 paired (pre/postintervention) plasma samples from early-stage breast cancer patients receiving limonene treatment (2 g QD) before surgical resection of their tumor. Metabolite profiling was conducted using ultra-performance liquid chromatography coupled to a linear trap quadrupole system and gas chromatography-mass spectrometry. Metabolites were identified by comparison of ion features in samples to a standard reference library. Pathway-based interpretation was conducted using the human metabolome database and the MetaCyc database. Of the 397 named metabolites identified, 72 changed significantly with limonene intervention. Class-based changes included significant decreases in adrenal steroids (P < 0.01), and significant increases in bile acids (P ≤ 0.05) and multiple collagen breakdown products (P < 0.001). The pattern of changes also suggested alterations in glucose metabolism. There were 47 metabolites whose change with intervention was significantly correlated to a decrease in cyclin D1, a cell-cycle regulatory protein, in patient tumor tissues (P ≤ 0.05). Here, oral administration of limonene resulted in significant changes in several metabolic pathways. Furthermore, pathway-based changes were related to the change in tissue level cyclin D1 expression. Future controlled clinical trials with limonene are necessary to determine the potential role and mechanisms of limonene in the breast cancer prevention setting. ©2014 American Association for Cancer Research.

Metabolomic profiling in the prediction of gestational diabetes mellitus

PubMed Central

Huynh, Jennifer; Xiong, Grace; Lee, Hang; Wenger, Julia; Clish, Clary; Nathan, David; Thadhani, Ravi; Gerszten, Robert

2015-01-01

Aims/hypothesis Metabolomic profiling in populations with impaired glucose tolerance has revealed that branched chain and aromatic amino acids (BCAAs) are predictive of type 2 diabetes. Because gestational diabetes mellitus (GDM) shares pathophysiological similarities with type 2 diabetes, the metabolite profile predictive of type 2 diabetes could potentially identify women who will develop GDM. Methods We conducted a nested case–control study of 18- to 40-year-old women who participated in the Massachusetts General Hospital Obstetrical Maternal Study between 1998 and 2007. Participants were enrolled during their first trimester of a singleton pregnancy and fasting serum samples were collected. The women were followed throughout pregnancy and identified as having GDM or normal glucose tolerance (NGT) in the third trimester. Women with GDM (n=96) were matched to women with NGT (n=96) by age, BMI, gravidity and parity. Liquid chromatography–mass spectrometry was used to measure the levels of 91 metabolites. Results Data analyses revealed the following characteristics (mean±SD): age 32.8±4.4 years, BMI 28.3±5.6 kg/m2, gravidity 2±1 and parity 1±1. Six metabolites (anthranilic acid, alanine, glutamate, creatinine, allantoin and serine) were identified as having significantly different levels between the two groups in conditional logistic regression analyses (p<0.05). The levels of the BCAAs did not differ significantly between GDM and NGT. Conclusions/interpretation Metabolic markers identified as being predictive of type 2 diabetes may not have the same predictive power for GDM. However, further study in a racially/ethnically diverse population-based cohort is necessary. PMID:25748329

Plasma metabolomics for the diagnosis and prognosis of H1N1 influenza pneumonia.

PubMed

Banoei, Mohammad M; Vogel, Hans J; Weljie, Aalim M; Kumar, Anand; Yende, Sachin; Angus, Derek C; Winston, Brent W

2017-04-19

Metabolomics is a tool that has been used for the diagnosis and prognosis of specific diseases. The purpose of this study was to examine if metabolomics could be used as a potential diagnostic and prognostic tool for H1N1 pneumonia. Our hypothesis was that metabolomics can potentially be used early for the diagnosis and prognosis of H1N1 influenza pneumonia. 1 H nuclear magnetic resonance spectroscopy and gas chromatography-mass spectrometry were used to profile the metabolome in 42 patients with H1N1 pneumonia, 31 ventilated control subjects in the intensive care unit (ICU), and 30 culture-positive plasma samples from patients with bacterial community-acquired pneumonia drawn within the first 24 h of hospital admission for diagnosis and prognosis of disease. We found that plasma-based metabolomics from samples taken within 24 h of hospital admission can be used to discriminate H1N1 pneumonia from bacterial pneumonia and nonsurvivors from survivors of H1N1 pneumonia. Moreover, metabolomics is a highly sensitive and specific tool for the 90-day prognosis of mortality in H1N1 pneumonia. This study demonstrates that H1N1 pneumonia can create a quite different plasma metabolic profile from bacterial culture-positive pneumonia and ventilated control subjects in the ICU on the basis of plasma samples taken within 24 h of hospital/ICU admission, early in the course of disease.

Biomarkers of Fatigue: Metabolomics Profiles Predictive of Cognitive Performance

DTIC Science & Technology

2013-05-01

metabolites. The latest version of the Human Metabolome Database (v. 2.5; released August , 2009) includes approximately 8,000 identified mammalian...monoamine oxidase; COMT , catechol-O-methyl transferase. (Modiefied from Rubí and Maechler, 2010). Ovals indicate metabolites found to be significantly

Metabolomics and Metabolic Diseases: Where Do We Stand?

PubMed

Newgard, Christopher B

2017-01-10

Metabolomics, or the comprehensive profiling of small molecule metabolites in cells, tissues, or whole organisms, has undergone a rapid technological evolution in the past two decades. These advances have led to the application of metabolomics to defining predictive biomarkers for incident cardiometabolic diseases and, increasingly, as a blueprint for understanding those diseases' pathophysiologic mechanisms. Progress in this area and challenges for the future are reviewed here. Copyright © 2017 Elsevier Inc. All rights reserved.

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

PubMed

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

2012-12-18

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

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

PubMed Central

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

2015-01-01

Untargeted metabolomics has the potential to improve the predictivity of in vitro toxicity models and therefore may aid the replacement of expensive and laborious animal models. Here we describe a long term repeat dose nephrotoxicity study conducted on the human renal proximal tubular epithelial cell line, RPTEC/TERT1, treated with 10 and 35 μmol·liter−1 of chloroacetaldehyde, a metabolite of the anti-cancer drug ifosfamide. Our study outlines the establishment of an automated and easy to use untargeted metabolomics workflow for HPLC-high resolution mass spectrometry data. Automated data analysis workflows based on open source software (OpenMS, KNIME) enabled a comprehensive and reproducible analysis of the complex and voluminous metabolomics data produced by the profiling approach. Time- and concentration-dependent responses were clearly evident in the metabolomic profiles. To obtain a more comprehensive picture of the mode of action, transcriptomics and proteomics data were also integrated. For toxicity profiling of chloroacetaldehyde, 428 and 317 metabolite features were detectable in positive and negative modes, respectively, after stringent removal of chemical noise and unstable signals. Changes upon treatment were explored using principal component analysis, and statistically significant differences were identified using linear models for microarray assays. The analysis revealed toxic effects only for the treatment with 35 μmol·liter−1 for 3 and 14 days. The most regulated metabolites were glutathione and metabolites related to the oxidative stress response of the cells. These findings are corroborated by proteomics and transcriptomics data, which show, among other things, an activation of the Nrf2 and ATF4 pathways. PMID:26055719

Updates in metabolomics tools and resources: 2014-2015.

PubMed

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

2016-01-01

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

A Direct Cell Quenching Method for Cell-Culture Based Metabolomics

EPA Science Inventory

A crucial step in metabolomic analysis of cellular extracts is the cell quenching process. The conventional method first uses trypsin to detach cells from their growth surface. This inevitably changes the profile of cellular metabolites since the detachment of cells from the extr...

Validation of Metabolomic, Diagnostic, and Prognostic Classifiers of Lung Cancer

DTIC Science & Technology

2016-10-01

information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this...Additionally, global metabolomic profiling will allow us to interrogate whether the military have unique exposures that may be related to lung cancer

Metabolomic and oxidative effects of quantum dots-indolicidin on three generations of Daphnia magna.

PubMed

Falanga, Annarita; Mercurio, Flavia A; Siciliano, Antonietta; Lombardi, Lucia; Galdiero, Stefania; Guida, Marco; Libralato, Giovanni; Leone, Marilisa; Galdiero, Emilia

2018-05-01

This study evaluated the effect of QDs functionalized with the antimicrobial peptide indolicidin on oxidative stress and metabolomics profiles of Daphnia magna across three generations (F0, F1, and F2). Exposing D. magna to sub-lethal concentrations of the complex QDs-indolicidin, a normal survival of daphnids was observed from F0 to F2, but a delay of first brood, fewer broods per female, a decrease of length of about 50% compared to control. In addition, QDs-indolicidin induced a significantly higher production of reactive oxygen species (ROS) gradually in each generation and an impairment of enzymes response to oxidative stress such as superoxide dismutase (SOD), catalase (CAT) and glutathione transferase (GST). Effects were confirmed by metabolomics profiles that pointed out a gradual decrease of metabolomics content over the three generations and a toxic effect of QDs-indolicidin likely related to the higher accumulation of ROS and decreased antioxidant capacity in F1 and F2 generations. Results highlighted the capability of metabolomics to reveal an early metabolic response to stress induced by environmental QDs-indolicidin complex. Copyright © 2018 Elsevier B.V. All rights reserved.

Metabolome analysis of Drosophila melanogaster during embryogenesis.

PubMed

An, Phan Nguyen Thuy; Yamaguchi, Masamitsu; Bamba, Takeshi; Fukusaki, Eiichiro

2014-01-01

The Drosophila melanogaster embryo has been widely utilized as a model for genetics and developmental biology due to its small size, short generation time, and large brood size. Information on embryonic metabolism during developmental progression is important for further understanding the mechanisms of Drosophila embryogenesis. Therefore, the aim of this study is to assess the changes in embryos' metabolome that occur at different stages of the Drosophila embryonic development. Time course samples of Drosophila embryos were subjected to GC/MS-based metabolome analysis for profiling of low molecular weight hydrophilic metabolites, including sugars, amino acids, and organic acids. The results showed that the metabolic profiles of Drosophila embryo varied during the course of development and there was a strong correlation between the metabolome and different embryonic stages. Using the metabolome information, we were able to establish a prediction model for developmental stages of embryos starting from their high-resolution quantitative metabolite composition. Among the important metabolites revealed from our model, we suggest that different amino acids appear to play distinct roles in different developmental stages and an appropriate balance in trehalose-glucose ratio is crucial to supply the carbohydrate source for the development of Drosophila embryo.

Metabolome Analysis of Drosophila melanogaster during Embryogenesis

PubMed Central

An, Phan Nguyen Thuy; Yamaguchi, Masamitsu; Bamba, Takeshi; Fukusaki, Eiichiro

2014-01-01

The Drosophila melanogaster embryo has been widely utilized as a model for genetics and developmental biology due to its small size, short generation time, and large brood size. Information on embryonic metabolism during developmental progression is important for further understanding the mechanisms of Drosophila embryogenesis. Therefore, the aim of this study is to assess the changes in embryos’ metabolome that occur at different stages of the Drosophila embryonic development. Time course samples of Drosophila embryos were subjected to GC/MS-based metabolome analysis for profiling of low molecular weight hydrophilic metabolites, including sugars, amino acids, and organic acids. The results showed that the metabolic profiles of Drosophila embryo varied during the course of development and there was a strong correlation between the metabolome and different embryonic stages. Using the metabolome information, we were able to establish a prediction model for developmental stages of embryos starting from their high-resolution quantitative metabolite composition. Among the important metabolites revealed from our model, we suggest that different amino acids appear to play distinct roles in different developmental stages and an appropriate balance in trehalose-glucose ratio is crucial to supply the carbohydrate source for the development of Drosophila embryo. PMID:25121768

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

PubMed Central

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

2016-01-01

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

Alteration of metabolomic markers of amino-acid metabolism in piglets with in-feed antibiotics.

PubMed

Mu, Chunlong; Yang, Yuxiang; Yu, Kaifan; Yu, Miao; Zhang, Chuanjian; Su, Yong; Zhu, Weiyun

2017-04-01

In-feed antibiotics have been used to promote growth in piglets, but its impact on metabolomics profiles associated with host metabolism is largely unknown. In this study, to test the hypothesis that antibiotic treatment may affect metabolite composition both in the gut and host biofluids, metabolomics profiles were analyzed in antibiotic-treated piglets. Piglets were fed a corn-soy basal diet with or without in-feed antibiotics from postnatal day 7 to day 42. The serum biochemical parameters, metabolomics profiles of the serum, urine, and jejunal digesta, and indicators of microbial metabolism (short-chain fatty acids and biogenic amines) were analyzed. Compared to the control group, antibiotics treatment did not have significant effects on serum biochemical parameters except that it increased (P < 0.05) the concentration of urea. Antibiotics treatment increased the relative concentrations of metabolites involved in amino-acid metabolism in the serum, while decreased the relative concentrations of most amino acids in the jejunal content. Antibiotics reduced urinary 2-ketoisocaproate and hippurate. Furthermore, antibiotics decreased (P < 0.05) the concentrations of propionate and butyrate in the feces. Antibiotics significantly affected the concentrations of biogenic amines, which are derived from microbial amino-acid metabolism. The three major amines, putrescine, cadaverine, and spermidine, were all increased (P < 0.05) in the large intestine of antibiotics-treated piglets. These results identified the phenomena that in-feed antibiotics may have significant impact on the metabolomic markers of amino-acid metabolism in piglets.

Vitamins, Metabolomics and Prostate Cancer

PubMed Central

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

2016-01-01

Purpose How micronutrients might influence risk of developing adenocarcinoma of the prostate has been the focus of a large body of research (especially regarding vitamins E, A, and D). Metabolomic profiling has the potential to discover molecular species relevant to prostate cancer etiology, early detection, and prevention, and may help elucidate the biologic mechanisms by which vitamins influence prostate cancer risk. Methods Prostate cancer risk data related to vitamins E, A, and D and metabolomics profiling from clinical, cohort, and nested case-control studies, along with randomized controlled trials, are examined and summarized, along with recent metabolomic data of the vitamin phenotypes. Results Higher vitamin E serologic status is associated with lower prostate cancer risk, and vitamin E genetic variant data support this. By contrast, controlled vitamin E supplementation trials have mixed results based on differing designs and dosages. Beta-carotene supplementation (in smokers) and higher circulating retinol and 25-hydroxy-vitamin D concentrations appear related to elevated prostate cancer risk. Our prospective metabolomics profiling of fasting serum collected 1-20 years prior to clinical diagnoses found lipid and energy/TCA cycle metabolites, including inositol-1-phosphate, lysolipids, alpha-ketoglutarate, and citrate, significantly associated with risk of aggressive disease. Conclusions Several active leads exist regarding the role of micronutrients and metabolites in prostate cancer carcinogenesis and risk. How vitamins D and A may adversely impact risk, and whether low-dose vitamin E supplementation remains a viable preventive approach, require further study. PMID:27339624

Vitamins, metabolomics, and prostate cancer.

PubMed

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

2017-06-01

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

NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in patients with colorectal cancer.

PubMed

Lin, Yan; Ma, Changchun; Liu, Chengkang; Wang, Zhening; Yang, Jurong; Liu, Xinmu; Shen, Zhiwei; Wu, Renhua

2016-05-17

Colorectal cancer (CRC) is a growing cause of mortality in developing countries, warranting investigation into its earlier detection for optimal disease management. A metabolomics based approach provides potential for noninvasive identification of biomarkers of colorectal carcinogenesis, as well as dissection of molecular pathways of pathophysiological conditions. Here, proton nuclear magnetic resonance spectroscopy (1HNMR) -based metabolomic approach was used to profile fecal metabolites of 68 CRC patients (stage I/II=20; stage III=25 and stage IV=23) and 32 healthy controls (HC). Pattern recognition through principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) was applied on 1H-NMR processed data for dimension reduction. OPLS-DA revealed that each stage of CRC could be clearly distinguished from HC based on their metabolomic profiles. Successive analyses identified distinct disturbances to fecal metabolites of CRC patients at various stages, compared with those in cancer free controls, including reduced levels of acetate, butyrate, propionate, glucose, glutamine, and elevated quantities of succinate, proline, alanine, dimethylglycine, valine, glutamate, leucine, isoleucine and lactate. These altered fecal metabolites potentially involved in the disruption of normal bacterial ecology, malabsorption of nutrients, increased glycolysis and glutaminolysis. Our findings revealed that the fecal metabolic profiles of healthy controls can be distinguished from CRC patients, even in the early stage (stage I/II), highlighting the potential utility of NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in CRC patients.

NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in patients with colorectal cancer

PubMed Central

Lin, Yan; Ma, Changchun; Liu, Chengkang; Wang, Zhening; Yang, Jurong; Liu, Xinmu; Shen, Zhiwei; Wu, Renhua

2016-01-01

Colorectal cancer (CRC) is a growing cause of mortality in developing countries, warranting investigation into its earlier detection for optimal disease management. A metabolomics based approach provides potential for noninvasive identification of biomarkers of colorectal carcinogenesis, as well as dissection of molecular pathways of pathophysiological conditions. Here, proton nuclear magnetic resonance spectroscopy (1HNMR) -based metabolomic approach was used to profile fecal metabolites of 68 CRC patients (stage I/II=20; stage III=25 and stage IV=23) and 32 healthy controls (HC). Pattern recognition through principal component analysis (PCA) and orthogonal partial least squares-discriminant analysis (OPLS-DA) was applied on 1H-NMR processed data for dimension reduction. OPLS-DA revealed that each stage of CRC could be clearly distinguished from HC based on their metabolomic profiles. Successive analyses identified distinct disturbances to fecal metabolites of CRC patients at various stages, compared with those in cancer free controls, including reduced levels of acetate, butyrate, propionate, glucose, glutamine, and elevated quantities of succinate, proline, alanine, dimethylglycine, valine, glutamate, leucine, isoleucine and lactate. These altered fecal metabolites potentially involved in the disruption of normal bacterial ecology, malabsorption of nutrients, increased glycolysis and glutaminolysis. Our findings revealed that the fecal metabolic profiles of healthy controls can be distinguished from CRC patients, even in the early stage (stage I/II), highlighting the potential utility of NMR-based fecal metabolomics fingerprinting as predictors of earlier diagnosis in CRC patients. PMID:27107423

Novel Applications of Metabolomics in Personalized Medicine: A Mini-Review.

PubMed

Li, Bingbing; He, Xuyun; Jia, Wei; Li, Houkai

2017-07-13

Interindividual variability in drug responses and disease susceptibility is common in the clinic. Currently, personalized medicine is highly valued, the idea being to prescribe the right medicine to the right patient. Metabolomics has been increasingly applied in evaluating the therapeutic outcomes of clinical drugs by correlating the baseline metabolic profiles of patients with their responses, i.e., pharmacometabonomics, as well as prediction of disease susceptibility among population in advance, i.e., patient stratification. The accelerated advance in metabolomics technology pinpoints the huge potential of its application in personalized medicine. In current review, we discussed the novel applications of metabolomics with typical examples in evaluating drug therapy and patient stratification, and underlined the potential of metabolomics in personalized medicine in the future.

How molecular profiling could revolutionize drug discovery.

PubMed

Stoughton, Roland B; Friend, Stephen H

2005-04-01

Information from genomic, proteomic and metabolomic measurements has already benefited target discovery and validation, assessment of efficacy and toxicity of compounds, identification of disease subgroups and the prediction of responses of individual patients. Greater benefits can be expected from the application of these technologies on a significantly larger scale; by simultaneously collecting diverse measurements from the same subjects or cell cultures; by exploiting the steadily improving quantitative accuracy of the technologies; and by interpreting the emerging data in the context of underlying biological models of increasing sophistication. The benefits of applying molecular profiling to drug discovery and development will include much lower failure rates at all stages of the drug development pipeline, faster progression from discovery through to clinical trials and more successful therapies for patient subgroups. Upheavals in existing organizational structures in the current 'conveyor belt' models of drug discovery might be required to take full advantage of these methods.

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

PubMed

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

2016-12-01

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

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

PubMed

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

2018-04-26

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

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

PubMed

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

2018-02-01

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

Metabolites Associated With Malnutrition in the Intensive Care Unit Are Also Associated With 28-Day Mortality.

PubMed

Mogensen, Kris M; Lasky-Su, Jessica; Rogers, Angela J; Baron, Rebecca M; Fredenburgh, Laura E; Rawn, James; Robinson, Malcolm K; Massarro, Anthony; Choi, Augustine M K; Christopher, Kenneth B

2017-02-01

We hypothesized that metabolic profiles would differ in critically ill patients with malnutrition relative to those without. We performed a prospective cohort study on 85 adult patients with systemic inflammatory response syndrome or sepsis admitted to a 20-bed medical intensive care unit (ICU) in Boston. We generated metabolomic profiles using gas and liquid chromatography and mass spectroscopy. We followed this by logistic regression and partial least squares discriminant analysis to identify individual metabolites that were significant. We then interrogated the entire metabolomics profile using metabolite set enrichment analysis and network model construction of chemical-protein target interactions to identify groups of metabolites and pathways that were differentiates in patients with and without malnutrition. Of the cohort, 38% were malnourished at admission to the ICU. Metabolomic profiles differed in critically ill patients with malnutrition relative to those without. Ten metabolites were significantly associated with malnutrition ( P < .05). A parsimonious model of 5 metabolites effectively differentiated patients with malnutrition (AUC = 0.76), including pyroglutamine and hypoxanthine. Using pathway enrichment analysis, we identified a critical role of glutathione and purine metabolism in predicting nutrition. Nutrition status was associated with 28-day mortality, even after adjustment for known phenotypic variables associated with ICU mortality. Importantly, 7 metabolites associated with nutrition status were also associated with 28-day mortality. Malnutrition is associated with differential metabolic profiles early in critical illness. Common to all of our metabolome analyses, glutathione and purine metabolism, which play principal roles in cellular redox regulation and accelerated tissue adenosine triphosphate degradation, respectively, were significantly altered with malnutrition.

Blood metabolome profiles of cattle colonized with Escherichia coli O157

USDA-ARS?s Scientific Manuscript database

Metabolomics is being increasingly used for diagnosis of asymptomatic/difficult-to-diagnose diseases in humans including parasitic (i.e. protozoan, schistosomal), viral (i.e. cytomegalovirus), bacterial (i.e. cystic fibrosis caused by Pseudomonas), genetic (i.e. autism) and cancer (i.e. gastric canc...

Bioinformatics/biostatistics: microarray analysis.

PubMed

Eichler, Gabriel S

2012-01-01

The quantity and complexity of the molecular-level data generated in both research and clinical settings require the use of sophisticated, powerful computational interpretation techniques. It is for this reason that bioinformatic analysis of complex molecular profiling data has become a fundamental technology in the development of personalized medicine. This chapter provides a high-level overview of the field of bioinformatics and outlines several, classic bioinformatic approaches. The highlighted approaches can be aptly applied to nearly any sort of high-dimensional genomic, proteomic, or metabolomic experiments. Reviewed technologies in this chapter include traditional clustering analysis, the Gene Expression Dynamics Inspector (GEDI), GoMiner (GoMiner), Gene Set Enrichment Analysis (GSEA), and the Learner of Functional Enrichment (LeFE).

Mass spectrometry in plant metabolomics strategies: from analytical platforms to data acquisition and processing.

PubMed

Ernst, Madeleine; Silva, Denise Brentan; Silva, Ricardo Roberto; Vêncio, Ricardo Z N; Lopes, Norberto Peporine

2014-06-01

Covering: up to 2013. Plant metabolomics is a relatively recent research field that has gained increasing interest in the past few years. Up to the present day numerous review articles and guide books on the subject have been published. This review article focuses on the current applications and limitations of the modern mass spectrometry techniques, especially in combination with electrospray ionisation (ESI), an ionisation method which is most commonly applied in metabolomics studies. As a possible alternative to ESI, perspectives on matrix-assisted laser desorption/ionisation mass spectrometry (MALDI-MS) in metabolomics studies are introduced, a method which still is not widespread in the field. In metabolomics studies the results must always be interpreted in the context of the applied sampling procedures as well as data analysis. Different sampling strategies are introduced and the importance of data analysis is illustrated in the example of metabolic network modelling.

Exposure to intrauterine inflammation alters metabolomic profiles in the amniotic fluid, fetal and neonatal brain in the mouse

PubMed Central

Barila, Guillermo O.; Hester, Michael S.; Elovitz, Michal A.

2017-01-01

Introduction Exposure to prenatal inflammation is associated with diverse adverse neurobehavioral outcomes in exposed offspring. The mechanism by which inflammation negatively impacts the developing brain is poorly understood. Metabolomic profiling provides an opportunity to identify specific metabolites, and novel pathways, which may reveal mechanisms by which exposure to intrauterine inflammation promotes fetal and neonatal brain injury. Therefore, we investigated whether exposure to intrauterine inflammation altered the metabolome of the amniotic fluid, fetal and neonatal brain. Additionally, we explored whether changes in the metabolomic profile from exposure to prenatal inflammation occurs in a sex-specific manner in the neonatal brain. Methods CD-1, timed pregnant mice received an intrauterine injection of lipopolysaccharide (50 μg/dam) or saline on embryonic day 15. Six and 48 hours later mice were sacrificed and amniotic fluid, and fetal brains were collected (n = 8/group). Postnatal brains were collected on day of life 1 (n = 6/group/sex). Global biochemical profiles were determined using ultra performance liquid chromatography/tandem mass spectrometry (Metabolon Inc.). Statistical analyses were performed by comparing samples from lipopolysaccharide and saline treated animals at each time point. For the P1 brains, analyses were stratified by sex. Results/Conclusions Exposure to intrauterine inflammation induced unique, temporally regulated changes in the metabolic profiles of amniotic fluid, fetal brain and postnatal brain. Six hours after exposure to intrauterine inflammation, the amniotic fluid and the fetal brain metabolomes were dramatically altered with significant enhancements of amino acid and purine metabolites. The amniotic fluid had enhanced levels of several members of the (hypo) xanthine pathway and this compound was validated as a potential biomarker. By 48 hours, the number of altered biochemicals in both the fetal brain and the amniotic fluid had declined, yet unique profiles existed. Neonatal pups exposed to intrauterine inflammation have significant alterations in their lipid metabolites, in particular, fatty acids. These sex-specific metabolic changes within the newborn brain offer an explanation regarding the sexual dimorphism of certain psychiatric and neurobehavioral disorders associated with exposure to prenatal inflammation. PMID:29049352

The Human Serum Metabolome

PubMed Central

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

2011-01-01

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

Metabolomics in chemical ecology.

PubMed

Kuhlisch, Constanze; Pohnert, Georg

2015-07-01

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

Microextraction by Packed Sorbent (MEPS) and Solid-Phase Microextraction (SPME) as Sample Preparation Procedures for the Metabolomic Profiling of Urine

PubMed Central

Silva, Catarina; Cavaco, Carina; Perestrelo, Rosa; Pereira, Jorge; Câmara, José S.

2014-01-01

For a long time, sample preparation was unrecognized as a critical issue in the analytical methodology, thus limiting the performance that could be achieved. However, the improvement of microextraction techniques, particularly microextraction by packed sorbent (MEPS) and solid-phase microextraction (SPME), completely modified this scenario by introducing unprecedented control over this process. Urine is a biological fluid that is very interesting for metabolomics studies, allowing human health and disease characterization in a minimally invasive form. In this manuscript, we will critically review the most relevant and promising works in this field, highlighting how the metabolomic profiling of urine can be an extremely valuable tool for the early diagnosis of highly prevalent diseases, such as cardiovascular, oncologic and neurodegenerative ones. PMID:24958388

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

PubMed

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

2015-01-01

Metabolomics has the potential to be a powerful and sensitive approach for investigating the low molecular weight metabolite profiles present in maternal fluids and their role in pregnancy. In this Data Note, LC-MS metabolome, lipidome and carnitine profiling data were collected from 180 healthy pregnant women, representing six time points spanning all three trimesters, and providing sufficient coverage to model the progression of normal pregnancy. As a relatively large scale, real-world dataset with robust numbers of quality control samples, the data are expected to prove useful for algorithm optimization and development, with the potential to augment studies into abnormal pregnancy. All data and ISA-TAB format enriched metadata are available for download in the MetaboLights and GigaScience databases.

Metabolomics discloses donor liver biomarkers associated with early allograft dysfunction.

PubMed

Cortes, Miriam; Pareja, Eugenia; García-Cañaveras, Juan C; Donato, M Teresa; Montero, Sandra; Mir, Jose; Castell, José V; Lahoz, Agustín

2014-09-01

Early allograft dysfunction (EAD) dramatically influences graft and patient outcome after orthotopic liver transplantation and its incidence is strongly determined by donor liver quality. Nevertheless, objective biomarkers, which can assess graft quality and anticipate organ function, are still lacking. This study aims to investigate whether there is a preoperative donor liver metabolomic biosignature associated with EAD. A comprehensive metabolomic profiling of 124 donor liver biopsies collected before transplantation was performed by mass spectrometry coupled to liquid chromatography. Donor liver grafts were classified into two groups: showing EAD and immediate graft function (IGF). Multivariate data analysis was used to search for the relationship between the metabolomic profiles present in donor livers before transplantation and their function in recipients. A set of liver graft dysfunction-associated biomarkers was identified. Key changes include significantly increased levels of bile acids, lysophospholipids, phospholipids, sphingomyelins and histidine metabolism products, all suggestive of disrupted lipid homeostasis and altered histidine pathway. Based on these biomarkers, a predictive EAD model was built and further evaluated by assessing 24 independent donor livers, yielding 91% sensitivity and 82% specificity. The model was also successfully challenged by evaluating donor livers showing primary non-function (n=4). A metabolomic biosignature that accurately differentiates donor livers, which later showed EAD or IGF, has been deciphered. The remarkable metabolomic differences between donor livers before transplant can relate to their different quality. The proposed metabolomic approach may become a clinical tool for donor liver quality assessment and for anticipating graft function before transplant. Copyright © 2014 European Association for the Study of the Liver. Published by Elsevier B.V. All rights reserved.

Comparative metabolomic and ionomic approach for abundant fishes in estuarine environments of Japan

PubMed Central

Yoshida, Seiji; Date, Yasuhiro; Akama, Makiko; Kikuchi, Jun

2014-01-01

Environmental metabolomics or ionomics is widely used to characterize the effects of environmental stressors on the health of aquatic organisms. However, most studies have focused on liver and muscle tissues of fish, and little is known about how the other organs are affected by environmental perturbations and effects such as metal pollutants or eutrophication. We examined the metabolic and mineral profiles of three kinds of abundant fishes in estuarine ecosystem, yellowfin goby, urohaze-goby, and juvenile Japanese seabass sampled from Tsurumi River estuary, Japan. Multivariate analyses, including nuclear magnetic resonance-based metabolomics and inductively coupled plasma optical emission spectrometry-based ionomics approaches, revealed that the profiles were clustered according to differences among body tissues rather than differences in body size, sex, and species. The metabolic and mineral profiles of the muscle and fin tissues, respectively, suggest that these tissues are most appropriate for evaluating environmental perturbations. Such analyses will be highly useful in evaluating the environmental variation and diversity in aquatic ecosystems. PMID:25387575

Serum Metabolic Profiling of Oocyst-Induced Toxoplasma gondii Acute and Chronic Infections in Mice Using Mass-Spectrometry

PubMed Central

Zhou, Chun-Xue; Cong, Wei; Chen, Xiao-Qing; He, Shen-Yi; Elsheikha, Hany M.; Zhu, Xing-Quan

2018-01-01

Toxoplasma gondii is an obligate intracellular parasite causing severe diseases in immunocompromised individuals and congenitally infected neonates, such as encephalitis and chorioretinitis. This study aimed to determine whether serum metabolic profiling can (i) identify metabolites associated with oocyst-induced T. gondii infection and (ii) detect systemic metabolic differences between T. gondii-infected mice and controls. We performed the first global metabolomics analysis of mice serum challenged with 100 sporulated T. gondii Pru oocysts (Genotype II). Sera from acutely infected mice (11 days post-infection, dpi), chronically infected mice (33 dpi) and control mice were collected and analyzed using LC-MS/MS platform. Following False Discovery Rate filtering, we identified 3871 and 2825 ions in ESI+ or ESI− mode, respectively. Principal Component Analysis (PCA) and Partial Least Squares Discriminant Analysis (PLS-DA) identified metabolomic profiles that clearly differentiated T. gondii-infected and -uninfected serum samples. Acute infection significantly influenced the serum metabolome. Our results identified common and uniquely perturbed metabolites and pathways. Acutely infected mice showed perturbations in metabolites associated with glycerophospholipid metabolism, biosynthesis of amino acid, and tyrosine metabolism. These findings demonstrated that acute T. gondii infection induces a global perturbation of mice serum metabolome, providing new insights into the mechanisms underlying systemic metabolic changes during early stage of T. gondii infection. PMID:29354104

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

PubMed

Luo, Xian; Li, Liang

2017-11-07

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

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

PubMed

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

2017-04-01

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

Whole grains beyond fibre: what can metabolomics tell us about mechanisms?

PubMed

Ross, Alastair B

2015-08-01

Dietary fibre alone does not fully explain the frequent association between greater intake of whole grains and reduced risk of disease in observational studies, and other phytochemicals or food structure may also play an important role. For all the observational evidence for the benefits of a whole-grain-rich diet, we have only limited knowledge of the mechanisms behind this reduction in disease risk, aside from the action of specific cereal fibres on reduction of blood cholesterol and the post-prandial glucose peak. Nutritional metabolomics, the global measurement and interpretation of metabolic profiles, assesses the interaction of food with the endogenous gene-protein cascade and the gut microbiome. This approach allows the generation of new hypotheses which account for systemic effects, rather than just focusing on one or two mechanisms or metabolic pathways. To date, animal and human trials using metabolomics to investigate mechanistic changes to metabolism on eating whole grains and cereal fractions have led to new hypotheses around mechanistic effects of whole grains. These include the role of cereals as a major source of dietary glycine betaine, a possible effect on phospholipid synthesis or metabolism, the role of branched-chain amino acids and improvements in insulin sensitivity, and the possibility that whole grains may have an effect on protein metabolism. These hypotheses help explain some of the observed effects of whole grains, although mechanistic studies using stable isotopes and fully quantitative measures are required to confirm these potential mechanisms.

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

PubMed Central

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

2015-01-01

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

Metabolomic Profiling of Plasma from Melioidosis Patients Using UHPLC-QTOF MS Reveals Novel Biomarkers for Diagnosis.

PubMed

Lau, Susanna K P; Lee, Kim-Chung; Lo, George C S; Ding, Vanessa S Y; Chow, Wang-Ngai; Ke, Tony Y H; Curreem, Shirly O T; To, Kelvin K W; Ho, Deborah T Y; Sridhar, Siddharth; Wong, Sally C Y; Chan, Jasper F W; Hung, Ivan F N; Sze, Kong-Hung; Lam, Ching-Wan; Yuen, Kwok-Yung; Woo, Patrick C Y

2016-02-27

To identify potential biomarkers for improving diagnosis of melioidosis, we compared plasma metabolome profiles of melioidosis patients compared to patients with other bacteremia and controls without active infection, using ultra-high-performance liquid chromatography-electrospray ionization-quadruple time-of-flight mass spectrometry. Principal component analysis (PCA) showed that the metabolomic profiles of melioidosis patients are distinguishable from bacteremia patients and controls. Using multivariate and univariate analysis, 12 significant metabolites from four lipid classes, acylcarnitine (n = 6), lysophosphatidylethanolamine (LysoPE) (n = 3), sphingomyelins (SM) (n = 2) and phosphatidylcholine (PC) (n = 1), with significantly higher levels in melioidosis patients than bacteremia patients and controls, were identified. Ten of the 12 metabolites showed area-under-receiver operating characteristic curve (AUC) >0.80 when compared both between melioidosis and bacteremia patients, and between melioidosis patients and controls. SM(d18:2/16:0) possessed the largest AUC when compared, both between melioidosis and bacteremia patients (AUC 0.998, sensitivity 100% and specificity 91.7%), and between melioidosis patients and controls (AUC 1.000, sensitivity 96.7% and specificity 100%). Our results indicate that metabolome profiling might serve as a promising approach for diagnosis of melioidosis using patient plasma, with SM(d18:2/16:0) representing a potential biomarker. Since the 12 metabolites were related to various pathways for energy and lipid metabolism, further studies may reveal their possible role in the pathogenesis and host response in melioidosis.

Metabolomic Profiling of Plasma from Melioidosis Patients Using UHPLC-QTOF MS Reveals Novel Biomarkers for Diagnosis

PubMed Central

Lau, Susanna K. P.; Lee, Kim-Chung; Lo, George C. S.; Ding, Vanessa S. Y.; Chow, Wang-Ngai; Ke, Tony Y. H.; Curreem, Shirly O. T.; To, Kelvin K. W.; Ho, Deborah T. Y.; Sridhar, Siddharth; Wong, Sally C. Y.; Chan, Jasper F. W.; Hung, Ivan F. N.; Sze, Kong-Hung; Lam, Ching-Wan; Yuen, Kwok-Yung; Woo, Patrick C. Y.

2016-01-01

To identify potential biomarkers for improving diagnosis of melioidosis, we compared plasma metabolome profiles of melioidosis patients compared to patients with other bacteremia and controls without active infection, using ultra-high-performance liquid chromatography-electrospray ionization-quadruple time-of-flight mass spectrometry. Principal component analysis (PCA) showed that the metabolomic profiles of melioidosis patients are distinguishable from bacteremia patients and controls. Using multivariate and univariate analysis, 12 significant metabolites from four lipid classes, acylcarnitine (n = 6), lysophosphatidylethanolamine (LysoPE) (n = 3), sphingomyelins (SM) (n = 2) and phosphatidylcholine (PC) (n = 1), with significantly higher levels in melioidosis patients than bacteremia patients and controls, were identified. Ten of the 12 metabolites showed area-under-receiver operating characteristic curve (AUC) >0.80 when compared both between melioidosis and bacteremia patients, and between melioidosis patients and controls. SM(d18:2/16:0) possessed the largest AUC when compared, both between melioidosis and bacteremia patients (AUC 0.998, sensitivity 100% and specificity 91.7%), and between melioidosis patients and controls (AUC 1.000, sensitivity 96.7% and specificity 100%). Our results indicate that metabolome profiling might serve as a promising approach for diagnosis of melioidosis using patient plasma, with SM(d18:2/16:0) representing a potential biomarker. Since the 12 metabolites were related to various pathways for energy and lipid metabolism, further studies may reveal their possible role in the pathogenesis and host response in melioidosis. PMID:26927094

The Karlsruhe Metabolomics and Nutrition (KarMeN) Study: Protocol and Methods of a Cross-Sectional Study to Characterize the Metabolome of Healthy Men and Women

PubMed Central

Kriebel, Anita; Dörr, Claudia; Bandt, Susanne; Rist, Manuela; Roth, Alexander; Hummel, Eva; Kulling, Sabine; Hoffmann, Ingrid; Watzl, Bernhard

2016-01-01

Background The human metabolome is influenced by various intrinsic and extrinsic factors. A precondition to identify such biomarkers is the comprehensive understanding of the composition and variability of the metabolome of healthy humans. Sample handling aspects have an important impact on the composition of the metabolome; therefore, it is crucial for any metabolomics study to standardize protocols on sample collection, preanalytical sample handling, storage, and analytics to keep the nonbiological variability as low as possible. Objective The main objective of the KarMeN study is to analyze the human metabolome in blood and urine by targeted and untargeted metabolite profiling (gas chromatography-mass spectrometry [GC-MS], GC×GC-MS, liquid chromatography-mass spectrometry [LC-MS/MS], and1H nuclear magnetic resonance [NMR] spectroscopy) and to determine the impact of sex, age, body composition, diet, and physical activity on metabolite profiles of healthy women and men. Here, we report the outline of the study protocol with special regard to all aspects that should be considered in studies applying metabolomics. Methods Healthy men and women, aged 18 years or older, were recruited. In addition to a number of anthropometric (height, weight, body mass index, waist circumference, body composition), clinical (blood pressure, electrocardiogram, blood and urine clinical chemistry) and functional parameters (lung function, arterial stiffness), resting metabolic rate, physical activity, fitness, and dietary intake were assessed, and 24-hour urine, fasting spot urine, and plasma samples were collected. Standard operating procedures were established for all steps of the study design. Using different analytical techniques (LC-MS, GC×GC-MS,1H NMR spectroscopy), metabolite profiles of urine and plasma were determined. Data will be analyzed using univariate and multivariate as well as predictive modeling methods. Results The project was funded in 2011 and enrollment was carried out between March 2012 and July 2013. A total of 301 volunteers were eligible to participate in the study. Metabolite profiling of plasma and urine samples has been completed and data analysis is currently underway. Conclusions We established the KarMeN study applying a broad set of clinical and physiological examinations with a high degree of standardization. Our experimental approach of combining scheduled timing of examinations and sampling with the multiplatform approach (GC×GC-MS, GC-MS, LC-MS/MS, and1H NMR spectroscopy) will enable us to differentiate between current and long-term effects of diet and physical activity on metabolite profiles, while enabling us at the same time to consider confounders such as age and sex in the KarMeN study. Trial Registration German Clinical Trials Register DRKS00004890; https://drks-neu.uniklinik-freiburg.de/drks_web/navigate.do? navigationId=trial.HTML&TRIAL_ID=DRKS00004890 (Archived by WebCite at http://www.webcitation.org/6iyM8dMtx) PMID:27421387

Cerebrospinal fluid metabolomic profiling in tuberculous and viral meningitis: Screening potential markers for differential diagnosis.

PubMed

Li, Zihui; Du, Boping; Li, Jing; Zhang, Jinli; Zheng, Xiaojing; Jia, Hongyan; Xing, Aiying; Sun, Qi; Liu, Fei; Zhang, Zongde

2017-03-01

Tuberculous meningitis (TBM) is the most severe and frequent form of central nervous system tuberculosis. The current lack of efficient diagnostic tests makes it difficult to differentiate TBM from other common types of meningitis, especially viral meningitis (VM). Metabolomics is an important tool to identify disease-specific biomarkers. However, little metabolomic information is available on adult TBM. We used 1 H nuclear magnetic resonance-based metabolomics to investigate the metabolic features of the CSF from 18 TBM and 20 VM patients. Principal component analysis and orthogonal signal correction-partial least squares-discriminant analysis (OSC-PLS-DA) were applied to analyze profiling data. Metabolites were identified using the Human Metabolome Database and pathway analysis was performed with MetaboAnalyst 3.0. The OSC-PLS-DA model could distinguish TBM from VM with high reliability. A total of 25 key metabolites that contributed to their discrimination were identified, including some, such as betaine and cyclohexane, rarely reported before in TBM. Pathway analysis indicated that amino acid and energy metabolism was significantly different in the CSF of TBM compared with VM. Twenty-five key metabolites identified in our study may be potential biomarkers for TBM differential diagnosis and are worthy of further investigation. Copyright © 2017 Elsevier B.V. All rights reserved.

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

PubMed Central

Fiehn, Oliver

2016-01-01

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

Influential Parameters for the Analysis of Intracellular Parasite Metabolomics.

PubMed

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

2018-04-25

Metabolomics is increasingly popular for the study of pathogens. For the malaria parasite Plasmodium falciparum , both targeted and untargeted metabolomics have improved our understanding of pathogenesis, host-parasite interactions, and antimalarial drug treatment and resistance. However, purification and analysis procedures for performing metabolomics on intracellular pathogens have not been explored. Here, we purified in vitro -grown ring-stage intraerythrocytic P. falciparum parasites for untargeted metabolomics studies; the small size of this developmental stage amplifies the challenges associated with metabolomics studies as the ratio between host and parasite biomass is maximized. Following metabolite identification and data preprocessing, we explored multiple confounding factors that influence data interpretation, including host contamination and normalization approaches (including double-stranded DNA, total protein, and parasite numbers). We conclude that normalization parameters have large effects on differential abundance analysis and recommend the thoughtful selection of these parameters. However, normalization does not remove the contribution from the parasite's extracellular environment (culture media and host erythrocyte). In fact, we found that extraparasite material is as influential on the metabolome as treatment with a potent antimalarial drug with known metabolic effects (artemisinin). Because of this influence, we could not detect significant changes associated with drug treatment. Instead, we identified metabolites predictive of host and medium contamination that could be used to assess sample purification. Our analysis provides the first quantitative exploration of the effects of these factors on metabolomics data analysis; these findings provide a basis for development of improved experimental and analytical methods for future metabolomics studies of intracellular organisms. IMPORTANCE Molecular characterization of pathogens such as the malaria parasite can lead to improved biological understanding and novel treatment strategies. However, the distinctive biology of the Plasmodium parasite, including its repetitive genome and the requirement for growth within a host cell, hinders progress toward these goals. Untargeted metabolomics is a promising approach to learn about pathogen biology. By measuring many small molecules in the parasite at once, we gain a better understanding of important pathways that contribute to the parasite's response to perturbations such as drug treatment. Although increasingly popular, approaches for intracellular parasite metabolomics and subsequent analysis are not well explored. The findings presented in this report emphasize the critical need for improvements in these areas to limit misinterpretation due to host metabolites and to standardize biological interpretation. Such improvements will aid both basic biological investigations and clinical efforts to understand important pathogens. Copyright © 2018 Carey et al.

Plasma metabolomic profiles of breast cancer patients after short-term limonene intervention

PubMed Central

Miller, Jessica A.; Pappan, Kirk; Thompson, Patricia A.; Want, Elizabeth J.; Siskos, Alexandros; Keun, Hector C.; Wulff, Jacob; Hu, Chengcheng; Lang, Julie E.; Chow, H-H. Sherry

2014-01-01

Limonene is a lipophilic monoterpene found in high levels in citrus peel. Limonene demonstrates anti-cancer properties in preclinical models with effects on multiple cellular targets at varying potency. While of interest as a cancer chemopreventive, the biological activity of limonene in humans is poorly understood. We conducted metabolite profiling in 39 paired (pre/post-intervention) plasma samples from early-stage breast cancer patients receiving limonene treatment (2 g QD) before surgical resection of their tumor. Metabolite profiling was conducted using ultra-performance liquid chromatography (UPLC) coupled to a linear trap quadrupole (LTQ) system and gas chromatography mass spectrometry (GC-MS). Metabolites were identified by comparison of ion features in samples to a standard reference library. Pathway-based interpretation was conducted using the human metabolome database (HMDB) and the MetaCyc database. Of the 397 named metabolites identified, 72 changed significantly with limonene intervention. Class-based changes included significant decreases in adrenal steroids (P’s<0.01), and significant increases in bile acids (P’s≤0.05) and multiple collagen breakdown products (P’s<0.001). The pattern of changes also suggested alterations in glucose metabolism. There were 47 metabolites whose change with intervention was significantly correlated to a decrease in cyclin D1, a cell cycle regulatory protein, in patient tumor tissues (P’s≤0.05). Here, oral administration of limonene resulted in significant changes in several metabolic pathways. Further, pathway-based changes were related to the change in tissue level cyclin D1 expression. Future controlled clinical trials with limonene are necessary to determine the potential role and mechanisms of limonene in the breast cancer prevention setting. PMID:25388013

Metabolomics Based Profiling of Dexamethasone Side Effects in Rats

PubMed Central

Malkawi, Abeer K.; Alzoubi, Karem H.; Jacob, Minnie; Matic, Goran; Ali, Asmaa; Al Faraj, Achraf; Almuhanna, Falah; Dasouki, Majed; Abdel Rahman, Anas M.

2018-01-01

Dexamethasone (Dex) is a synthetic glucocorticoid that has anti-inflammatory and immunosuppressant effects and is used in several conditions such as asthma and severe allergy. Patients receiving Dex, either at a high dose or for a long time, might develop several side effects such as hyperglycemia, weight change, or osteoporosis due to its in vivo non-selectivity. Herein, we used liquid chromatography-tandem mass spectrometry-based comprehensive targeted metabolomic profiling as well as radiographic imaging techniques to study the side effects of Dex treatment in rats. The Dex-treated rats suffered from a ∼20% reduction in weight gain, hyperglycemia (145 mg/dL), changes in serum lipids, and reduction in total serum alkaline phosphatase (ALP) (∼600 IU/L). Also, compared to controls, Dex-treated rats showed a distinctive metabolomics profile. In particular, serum amino acids metabolism showed six-fold reduction in phenylalanine, lysine, and arginine levels and upregulation of tyrosine and hydroxyproline reflecting perturbations in gluconeogenesis and protein catabolism which together lead to weight loss and abnormal bone metabolism. Sorbitol level was markedly elevated secondary to hyperglycemia and reflecting activation of the polyol metabolism pathway causing a decrease in the availability of reducing molecules (glutathione, NADPH, NAD+). Overexpression of succinylacetone (4,6-dioxoheptanoic acid) suggests a novel inhibitory effect of Dex on hepatic fumarylacetoacetate hydrolase. The acylcarnitines, mainly the very long chain species (C12, C14:1, C18:1) were significantly increased after Dex treatment which reflects degradation of the adipose tissue. In conclusion, long-term Dex therapy in rats is associated with a distinctive metabolic profile which correlates with its side effects. Therefore, metabolomics based profiling may predict Dex treatment-related side effects and may offer possible novel therapeutic interventions. PMID:29503615

Metabolomics Based Profiling of Dexamethasone Side Effects in Rats.

PubMed

Malkawi, Abeer K; Alzoubi, Karem H; Jacob, Minnie; Matic, Goran; Ali, Asmaa; Al Faraj, Achraf; Almuhanna, Falah; Dasouki, Majed; Abdel Rahman, Anas M

2018-01-01

Dexamethasone (Dex) is a synthetic glucocorticoid that has anti-inflammatory and immunosuppressant effects and is used in several conditions such as asthma and severe allergy. Patients receiving Dex, either at a high dose or for a long time, might develop several side effects such as hyperglycemia, weight change, or osteoporosis due to its in vivo non-selectivity. Herein, we used liquid chromatography-tandem mass spectrometry-based comprehensive targeted metabolomic profiling as well as radiographic imaging techniques to study the side effects of Dex treatment in rats. The Dex-treated rats suffered from a ∼20% reduction in weight gain, hyperglycemia (145 mg/dL), changes in serum lipids, and reduction in total serum alkaline phosphatase (ALP) (∼600 IU/L). Also, compared to controls, Dex-treated rats showed a distinctive metabolomics profile. In particular, serum amino acids metabolism showed six-fold reduction in phenylalanine, lysine, and arginine levels and upregulation of tyrosine and hydroxyproline reflecting perturbations in gluconeogenesis and protein catabolism which together lead to weight loss and abnormal bone metabolism. Sorbitol level was markedly elevated secondary to hyperglycemia and reflecting activation of the polyol metabolism pathway causing a decrease in the availability of reducing molecules (glutathione, NADPH, NAD + ). Overexpression of succinylacetone (4,6-dioxoheptanoic acid) suggests a novel inhibitory effect of Dex on hepatic fumarylacetoacetate hydrolase. The acylcarnitines, mainly the very long chain species (C12, C14:1, C18:1) were significantly increased after Dex treatment which reflects degradation of the adipose tissue. In conclusion, long-term Dex therapy in rats is associated with a distinctive metabolic profile which correlates with its side effects. Therefore, metabolomics based profiling may predict Dex treatment-related side effects and may offer possible novel therapeutic interventions.

Urine-based Metabolomics with Fish: Use of Repeat Sampling (of an individual) to Non-lethally Assess Temporal Effects of Contaminants

EPA Science Inventory

Environmental metabolomics is a rapidly developing field for assessing the global metabolite profiles of tissues and/or biofluids from ecologically relevant organisms to identify biomarkers of exposure to various stressors, elucidate a chemical’s mode(s)-of-action, and decipher t...

Metabolomic Insight into Lipid and Protein Profile in Diabetes Using Mass Spectrometry.

PubMed

Bukowiecka-Matusiak, Malgorzata; Chmielewska-Kassassir, Malgorzata; Szczesna, Dorota; Wozniak, Lucyna A

2016-01-01

In recent years, metabolomics has become a necessary tool for understanding the impact of external and pathological factors on the operation of biological systems. The first reports of metabolomics date back to the 1970s, however, the area only began to develop dynamically at the beginning of this century and has proved effective only during the present decade. The five primary tools used in this form of analysis are NMR spectrometry, HPLC, TLC-UV, GC-MS and LC-MS/MS, with MS as the most universal approach, particularly when used together with chromatographic separation and NMR. Diabetes mellitus type 2 (T2DM) is a rapidly growing problem with global consequences. The metabolomic approach has been extensively applied to examining T2DM, insulin resistance and obesity, not only to assess the development of the disease, but also to discover its potential biomarkers. The presented review summarizes current studies on lipidomic and proteomic profiles in the context of different types of diabetes mellitus disease (T1DM, T2DM and GDM), as determined by chromatography-coupled mass spectrometry.

Metabolomic approach for discrimination of processed ginseng genus (Panax ginseng and Panax quinquefolius) using UPLC-QTOF MS

PubMed Central

Park, Hee-Won; In, Gyo; Kim, Jeong-Han; Cho, Byung-Goo; Han, Gyeong-Ho; Chang, Il-Moo

2013-01-01

Discriminating between two herbal medicines (Panax ginseng and Panax quinquefolius), with similar chemical and physical properties but different therapeutic effects, is a very serious and difficult problem. Differentiation between two processed ginseng genera is even more difficult because the characteristics of their appearance are very similar. An ultraperformance liquid chromatography-quadrupole time-of-flight mass spectrometry (UPLC-QTOF MS)-based metabolomic technique was applied for the metabolite profiling of 40 processed P. ginseng and processed P. quinquefolius. Currently known biomarkers such as ginsenoside Rf and F11 have been used for the analysis using the UPLC-photodiode array detector. However, this method was not able to fully discriminate between the two processed ginseng genera. Thus, an optimized UPLC-QTOF-based metabolic profiling method was adapted for the analysis and evaluation of two processed ginseng genera. As a result, all known biomarkers were identified by the proposed metabolomics, and additional potential biomarkers were extracted from the huge amounts of global analysis data. Therefore, it is expected that such metabolomics techniques would be widely applied to the ginseng research field. PMID:24558312

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

PubMed

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

2015-04-01

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

Methods, applications and concepts of metabolite profiling: primary metabolism.

PubMed

Steinhauser, Dirk; Kopka, Joachim

2007-01-01

In the 1990s the concept of a comprehensive analysis of the metabolic complement in biological systems, termed metabolomics or alternately metabonomics, was established as the last of four cornerstones for phenotypic studies in the post-genomic era. With genomic, transcriptomic, and proteomic technologies in place and metabolomic phenotyping under rapid development all necessary tools appear to be available today for a fully functional assessment of biological phenomena at all major system levels of life. This chapter attempts to describe and discuss crucial steps of establishing and maintaining a gas chromatography/electron impact ionization/ mass spectrometry (GC-EI-MS)-based metabolite profiling platform. GC-EI-MS can be perceived as the first and exemplary profiling technology aimed at simultaneous and non-biased analysis of primary metabolites from biological samples. The potential and constraints of this profiling technology are among the best understood. Most problems are solved as well as pitfalls identified. Thus GC-EI-MS serves as an ideal example for students and scientists who intend to enter the field of metabolomics. This chapter will be biased towards GC-EI-MS analyses but aims at discussing general topics, such as experimental design, metabolite identification, quantification and data mining.

Influence of yeast and lactic acid bacterium on the constituent profile of soy sauce during fermentation.

PubMed

Harada, Risa; Yuzuki, Masanobu; Ito, Kotaro; Shiga, Kazuki; Bamba, Takeshi; Fukusaki, Eiichiro

2017-02-01

Soy sauce is a Japanese traditional seasoning composed of various constituents that are produced by various microbes during a long-term fermentation process. Due to the complexity of the process, the investigation of the constituent profile during fermentation is difficult. Metabolomics, the comprehensive study of low molecular weight compounds in biological samples, is thought to be a promising strategy for deep understanding of the constituent contribution to food flavor characteristics. Therefore, metabolomics is suitable for the analysis of soy sauce fermentation. Unfortunately, only few and unrefined studies of soy sauce fermentation using metabolomics approach have been reported. Therefore, we investigated changes in low molecular weight hydrophilic and volatile compounds of soy sauce using gas chromatography/mass spectrometry (GC/MS)-based non-targeted metabolic profiling. The data were analyzed by statistical analysis to evaluate influences of yeast and lactic acid bacterium on the constituent profile. Consequently, our results suggested a novel finding that lactic acid bacterium affected the production of several constituents such as cyclotene, furfural, furfuryl alcohol and methional in the soy sauce fermentation process. Copyright © 2016 The Society for Biotechnology, Japan. Published by Elsevier B.V. All rights reserved.

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

PubMed

Mung, Dorothea; Li, Liang

2017-04-18

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

Metabolomic Studies of Oral Biofilm, Oral Cancer, and Beyond

PubMed Central

Washio, Jumpei; Takahashi, Nobuhiro

2016-01-01

Oral diseases are known to be closely associated with oral biofilm metabolism, while cancer tissue is reported to possess specific metabolism such as the ‘Warburg effect’. Metabolomics might be a useful method for clarifying the whole metabolic systems that operate in oral biofilm and oral cancer, however, technical limitations have hampered such research. Fortunately, metabolomics techniques have developed rapidly in the past decade, which has helped to solve these difficulties. In vivo metabolomic analyses of the oral biofilm have produced various findings. Some of these findings agreed with the in vitro results obtained in conventional metabolic studies using representative oral bacteria, while others differed markedly from them. Metabolomic analyses of oral cancer tissue not only revealed differences between metabolomic profiles of cancer and normal tissue, but have also suggested a specific metabolic system operates in oral cancer tissue. Saliva contains a variety of metabolites, some of which might be associated with oral or systemic disease; therefore, metabolomics analysis of saliva could be useful for identifying disease-specific biomarkers. Metabolomic analyses of the oral biofilm, oral cancer, and saliva could contribute to the development of accurate diagnostic, techniques, safe and effective treatments, and preventive strategies for oral and systemic diseases. PMID:27271597

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

PubMed

Washio, Jumpei; Takahashi, Nobuhiro

2016-06-02

Oral diseases are known to be closely associated with oral biofilm metabolism, while cancer tissue is reported to possess specific metabolism such as the 'Warburg effect'. Metabolomics might be a useful method for clarifying the whole metabolic systems that operate in oral biofilm and oral cancer, however, technical limitations have hampered such research. Fortunately, metabolomics techniques have developed rapidly in the past decade, which has helped to solve these difficulties. In vivo metabolomic analyses of the oral biofilm have produced various findings. Some of these findings agreed with the in vitro results obtained in conventional metabolic studies using representative oral bacteria, while others differed markedly from them. Metabolomic analyses of oral cancer tissue not only revealed differences between metabolomic profiles of cancer and normal tissue, but have also suggested a specific metabolic system operates in oral cancer tissue. Saliva contains a variety of metabolites, some of which might be associated with oral or systemic disease; therefore, metabolomics analysis of saliva could be useful for identifying disease-specific biomarkers. Metabolomic analyses of the oral biofilm, oral cancer, and saliva could contribute to the development of accurate diagnostic, techniques, safe and effective treatments, and preventive strategies for oral and systemic diseases.

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

PubMed

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

2013-04-01

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

Plasma Metabolomic Profiling Suggests Early Indications for Predisposition to Latent Insulin Resistance in Children Conceived by ICSI

PubMed Central

Margeli, Alexandra; Mantzou, Emilia; Konsta, Maria; Loutradis, Dimitrios; Mastorakos, George; Papassotiriou, Ioannis; Klapa, Maria I.; Kanaka-Gantenbein, Christina; Chrousos, George P.

2014-01-01

Background There have been increasing indications about an epigenetically-based elevated predisposition of assisted reproductive technology (ART) offspring to insulin resistance, which can lead to an unfavorable cardio-metabolic profile in adult life. However, the relevant long-term systematic molecular studies are limited, especially for the IntraCytoplasmic Sperm Injection (ICSI) method, introduced in 1992. In this study, we carefully defined a group of 42 prepubertal ICSI and 42 naturally conceived (NC) children. We assessed differences in their metabolic profile based on biochemical measurements, while, for a subgroup, plasma metabolomic analysis was also performed, investigating any relevant insulin resistance indices. Methods & Results Auxological and biochemical parameters of 42 6.8±2.1 yrs old ICSI-conceived and 42 age-matched controls were measured. Significant differences between the groups were determined using univariate and multivariate statistics, indicating low urea and low-grade inflammation markers (YKL-40, hsCRP) and high triiodothyronine (T3) in ICSI-children compared to controls. Moreover, plasma metabolomic analysis carried out for a subgroup of 10 ICSI- and 10 NC girls using Gas Chromatography-Mass Spectrometry (GC-MS) indicated clear differences between the two groups, characterized by 36 metabolites linked to obesity, insulin resistance and metabolic syndrome. Notably, the distinction between the two girl subgroups was accentuated when both their biochemical and metabolomic measurements were employed. Conclusions The present study contributes a large auxological and biochemical dataset of a well-defined group of pre-pubertal ICSI-conceived subjects to the research of the ART effect to the offspring's health. Moreover, it is the first time that the relevant usefulness of metabolomics was investigated. The acquired results are consistent with early insulin resistance in ICSI-offspring, paving the way for further systematic investigations. These data support that metabolomics may unravel metabolic differences before they become clinically or biochemically evident, underlining its utility in the ART research. PMID:24728198

Serum Metabolomic Profiling in Acute Alcoholic Hepatitis Identifies Multiple Dysregulated Pathways

PubMed Central

Rachakonda, Vikrant; Gabbert, Charles; Raina, Amit; Bell, Lauren N.; Cooper, Sara; Malik, Shahid; Behari, Jaideep

2014-01-01

Background and Objectives While animal studies have implicated derangements of global energy homeostasis in the pathogenesis of acute alcoholic hepatitis (AAH), the relevance of these findings to the development of human AAH remains unclear. Using global, unbiased serum metabolomics analysis, we sought to characterize alterations in metabolic pathways associated with severe AAH and identify potential biomarkers for disease prognosis. Methods This prospective, case-control study design included 25 patients with severe AAH and 25 ambulatory patients with alcoholic cirrhosis. Serum samples were collected within 24 hours of the index clinical encounter. Global, unbiased metabolomics profiling was performed. Patients were followed for 180 days after enrollment to determine survival. Results Levels of 234 biochemicals were altered in subjects with severe AAH. Random-forest analysis, principal component analysis, and integrated hierarchical clustering methods demonstrated that metabolomics profiles separated the two cohorts with 100% accuracy. Severe AAH was associated with enhanced triglyceride lipolysis, impaired mitochondrial fatty acid beta oxidation, and upregulated omega oxidation. Low levels of multiple lysolipids and related metabolites suggested decreased plasma membrane remodeling in severe AAH. While most measured bile acids were increased in severe AAH, low deoxycholate and glycodeoxycholate levels indicated intestinal dysbiosis. Several changes in substrate utilization for energy homeostasis were identified in severe AAH, including increased glucose consumption by the pentose phosphate pathway, altered tricarboxylic acid (TCA) cycle activity, and enhanced peptide catabolism. Finally, altered levels of small molecules related to glutathione metabolism and antioxidant vitamin depletion were observed in patients with severe AAH. Univariable logistic regression revealed 15 metabolites associated with 180-day survival in severe AAH. Conclusion Severe AAH is characterized by a distinct metabolic phenotype spanning multiple pathways. Metabolomics profiling revealed a panel of biomarkers for disease prognosis, and future studies are planned to validate these findings in larger cohorts of patients with severe AAH. PMID:25461442

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

PubMed Central

Luck, Margaux M.; Le Moyec, Laurence; Barrey, Eric; Triba, Mohamed N.; Bouchemal, Nadia; Savarin, Philippe; Robert, Céline

2015-01-01

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 cros-validated ANOVA p < 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 < 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. PMID:26347654

Metabolite Profiling of Feces and Serum in Hemodialysis Patients and the Effect of Medicinal Charcoal Tablets.

PubMed

Liu, Sixiu; Liang, Shanshan; Liu, Hua; Chen, Lei; Sun, Lingshuang; Wei, Meng; Jiang, Hongli; Wang, Jing

2018-05-22

Recently, the colon has been recognized as an important source of various uremic toxins in patients with end stage renal disease. Medicinal charcoal tablets are an oral adsorbent that are widely used in patients with chronic kidney disease in China to remove creatinine and urea from the colon. A parallel fecal and serum metabolomics study was performed to determine comprehensive metabolic profiles of patients receiving hemodialysis (HD). The effects of medicinal charcoal tablets on the fecal and serum metabolomes of HD patients were also investigated. Ultra-performance liquid chromatography/mass spectrometry was used to investigate the fecal and serum metabolic profiles of 20 healthy controls and 31 HD patients before and after taking medicinal charcoal tablets for 3 months. There were distinct metabolic variations between the HD patients and healthy controls both in the feces and serum according to multivariate data analysis. Metabolic disturbances of alanine, aspartate and glutamate metabolism, arginine and proline metabolism figured prominently in the serum. However, in the feces, alterations of tryptophan metabolism, lysine degradation and beta-alanine metabolism were pronounced, and the levels of several amino acids (leucine, phenylalanine, lysine, histidine, methionine, tyrosine, and tryptophan) were increased dramatically. Nineteen fecal metabolites and 21 serum metabolites were also identified as biomarkers that contributed to the metabolic differences. Additionally, medicinal charcoal treatment generally enabled the serum and fecal metabolomes of the HD patients to draw close to those of the control subjects, especially the serum metabolic profile. Parallel fecal and serum metabolomics uncovered the systematic metabolic variations of HD patients, especially disturbances in amino acid metabolism in the colon. Medicinal charcoal tablets had an impact on the serum and fecal metabolomes of HD patients, but their exact effects still need to be studied further. © 2018 The Author(s). Published by S. Karger AG, Basel.

MWASTools: an R/bioconductor package for metabolome-wide association studies.

PubMed

Rodriguez-Martinez, Andrea; Posma, Joram M; Ayala, Rafael; Neves, Ana L; Anwar, Maryam; Petretto, Enrico; Emanueli, Costanza; Gauguier, Dominique; Nicholson, Jeremy K; Dumas, Marc-Emmanuel

2018-03-01

MWASTools is an R package designed to provide an integrated pipeline to analyse metabonomic data in large-scale epidemiological studies. Key functionalities of our package include: quality control analysis; metabolome-wide association analysis using various models (partial correlations, generalized linear models); visualization of statistical outcomes; metabolite assignment using statistical total correlation spectroscopy (STOCSY); and biological interpretation of metabolome-wide association studies results. The MWASTools R package is implemented in R (version  > =3.4) and is available from Bioconductor: https://bioconductor.org/packages/MWASTools/. m.dumas@imperial.ac.uk. Supplementary data are available at Bioinformatics online. © The Author(s) 2017. Published by Oxford University Press.

Metabolome of human gut microbiome is predictive of host dysbiosis.

PubMed

Larsen, Peter E; Dai, Yang

2015-01-01

Humans live in constant and vital symbiosis with a closely linked bacterial ecosystem called the microbiome, which influences many aspects of human health. When this microbial ecosystem becomes disrupted, the health of the human host can suffer; a condition called dysbiosis. However, the community compositions of human microbiomes also vary dramatically from individual to individual, and over time, making it difficult to uncover the underlying mechanisms linking the microbiome to human health. We propose that a microbiome's interaction with its human host is not necessarily dependent upon the presence or absence of particular bacterial species, but instead is dependent on its community metabolome; an emergent property of the microbiome. Using data from a previously published, longitudinal study of microbiome populations of the human gut, we extrapolated information about microbiome community enzyme profiles and metabolome models. Using machine learning techniques, we demonstrated that the aggregate predicted community enzyme function profiles and modeled metabolomes of a microbiome are more predictive of dysbiosis than either observed microbiome community composition or predicted enzyme function profiles. Specific enzyme functions and metabolites predictive of dysbiosis provide insights into the molecular mechanisms of microbiome-host interactions. The ability to use machine learning to predict dysbiosis from microbiome community interaction data provides a potentially powerful tool for understanding the links between the human microbiome and human health, pointing to potential microbiome-based diagnostics and therapeutic interventions.

Metabolome of human gut microbiome is predictive of host dysbiosis

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

Larsen, Peter E.; Dai, Yang

Background: Humans live in constant and vital symbiosis with a closely linked bacterial ecosystem called the microbiome, which influences many aspects of human health. When this microbial ecosystem becomes disrupted, the health of the human host can suffer; a condition called dysbiosis. The community compositions of human microbiomes also vary dramatically from individual to individual, and over time, making it difficult to uncover the underlying mechanisms linking the microbiome to human health. We propose that a microbiome’s interaction with its human host is not necessarily dependent upon the presence or absence of particular bacterial species, but instead is dependent onmore » its community metabolome; an emergent property of the microbiome. Results: Using data from a previously published, longitudinal study of microbiome populations of the human gut, we extrapolated information about microbiome community enzyme profiles and metabolome models. Using machine learning techniques, we demonstrated that the aggregate predicted community enzyme function profiles and modeled metabolomes of a microbiome are more predictive of dysbiosis than either observed microbiome community composition or predicted enzyme function profiles. Conclusions: Specific enzyme functions and metabolites predictive of dysbiosis provide insights into the molecular mechanisms of microbiome–host interactions. The ability to use machine learning to predict dysbiosis from microbiome community interaction data provides a potentially powerful tool for understanding the links between the human microbiome and human health, pointing to potential microbiome-based diagnostics and therapeutic interventions.« less

Metabolome of human gut microbiome is predictive of host dysbiosis

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

Larsen, Peter E.; Dai, Yang

Background: Humans live in constant and vital symbiosis with a closely linked bacterial ecosystem called the microbiome, which influences many aspects of human health. When this microbial ecosystem becomes disrupted, the health of the human host can suffer; a condition called dysbiosis. However, the community compositions of human microbiomes also vary dramatically from individual to individual, and over time, making it difficult to uncover the underlying mechanisms linking the microbiome to human health. We propose that a microbiome’s interaction with its human host is not necessarily dependent upon the presence or absence of particular bacterial species, but instead is dependentmore » on its community metabolome; an emergent property of the microbiome. Results: Using data from a previously published, longitudinal study of microbiome populations of the human gut, we extrapolated information about microbiome community enzyme profiles and metabolome models. Using machine learning techniques, we demonstrated that the aggregate predicted community enzyme function profiles and modeled metabolomes of a microbiome are more predictive of dysbiosis than either observed microbiome community composition or predicted enzyme function profiles. Conclusions: Specific enzyme functions and metabolites predictive of dysbiosis provide insights into the molecular mechanisms of microbiome–host interactions. The ability to use machine learning to predict dysbiosis from microbiome community interaction data provides a potentially powerful tool for understanding the links between the human microbiome and human health, pointing to potential microbiome-based diagnostics and therapeutic interventions.« less

Metabolome of human gut microbiome is predictive of host dysbiosis

DOE PAGES

Larsen, Peter E.; Dai, Yang

2015-09-14

Background: Humans live in constant and vital symbiosis with a closely linked bacterial ecosystem called the microbiome, which influences many aspects of human health. When this microbial ecosystem becomes disrupted, the health of the human host can suffer; a condition called dysbiosis. The community compositions of human microbiomes also vary dramatically from individual to individual, and over time, making it difficult to uncover the underlying mechanisms linking the microbiome to human health. We propose that a microbiome’s interaction with its human host is not necessarily dependent upon the presence or absence of particular bacterial species, but instead is dependent onmore » its community metabolome; an emergent property of the microbiome. Results: Using data from a previously published, longitudinal study of microbiome populations of the human gut, we extrapolated information about microbiome community enzyme profiles and metabolome models. Using machine learning techniques, we demonstrated that the aggregate predicted community enzyme function profiles and modeled metabolomes of a microbiome are more predictive of dysbiosis than either observed microbiome community composition or predicted enzyme function profiles. Conclusions: Specific enzyme functions and metabolites predictive of dysbiosis provide insights into the molecular mechanisms of microbiome–host interactions. The ability to use machine learning to predict dysbiosis from microbiome community interaction data provides a potentially powerful tool for understanding the links between the human microbiome and human health, pointing to potential microbiome-based diagnostics and therapeutic interventions.« less

Metabolomic Profiling of Soybeans (Glycine Max L.) Reveals Importance of Sugar and Nitogen Metabolisms under Drought and Heat Stress

USDA-ARS?s Scientific Manuscript database

Soybean, an important legume crop, is continually threatened by abiotic stresses, especially drought and heat stress. At molecular levels, reduced yields due to drought and heat stress can be seen in the alterations of metabolic homeostasis of vegetative tissues. A global metabolomics approach can b...

Commentary on: "An integrated metabolic atlas of clear cell renal cell carcinoma." Hakimi AA, Reznik E, Lee CH, Creighton CJ, Brannon AR, Luna A, Aksoy BA, Liu EM, Shen R, Lee W, Chen Y, Stirdivant SM, Russo P, Chen YB, Tickoo SK, Reuter VE, Cheng EH, Sander C, Hsieh JJ.: Cancer Cell. 2016 Jan 11;29(1):104-16.

PubMed

Lee, Byron H

2017-09-01

Dysregulated metabolism is a hallmark of cancer, manifested through alterations in metabolites. We performed metabolomic profiling on 138 matched clear cell renal cell carcinoma (ccRCC)/normal tissue pairs and found that ccRCC is characterized by broad shifts in central carbon metabolism, one-carbon metabolism, and antioxidant response. Tumor progression and metastasis were associated with metabolite increases in glutathione and cysteine/methionine metabolism pathways. We develop an analytic pipeline and visualization tool (metabolograms) to bridge the gap between TCGA transcriptomic profiling and our metabolomic data, which enables us to assemble an integrated pathway-level metabolic atlas and to demonstrate discordance between transcriptome and metabolome. Lastly, expression profiling was performed on a high-glutathione cluster, which corresponds to a poor-survival subgroup in the ccRCC TCGA cohort. Copyright © 2017 Elsevier Inc. All rights reserved.

Metabolites as Biomarkers of Adverse Reactions Following Vaccination: A Pilot Study using Nuclear Magnetic Resonance Metabolomics

PubMed Central

McClenathan, Bruce M.; Stewart, Delisha A.; Spooner, Christina E.; Pathmasiri, Wimal W.; Burgess, Jason P.; McRitchie, Susan L.; Choi, Y. Sammy; Sumner, Susan C.J.

2017-01-01

An Adverse Event Following Immunization (AEFI) is an adverse reaction to a vaccination that goes above and beyond the usual side effects associated with vaccinations. One serious AEFI related to the smallpox vaccine is myopericarditis. Metabolomics involves the study of the low molecular weight metabolite profile of cells, tissues, and biological fluids, and provides a functional readout of the phenotype. Metabolomics may help identify a particular metabolic signature in serum of subjects who are predisposed to developing AEFIs. The goal of this study was to identify metabolic markers that may predict the development of adverse events following smallpox vaccination. Serum samples were collected from military personnel prior to and following receipt of smallpox vaccine. The study population included five subjects who were clinically diagnosed with myopericarditis, 30 subjects with asymptomatic elevation of troponins, and 31 subjects with systemic symptoms following immunization, and 34 subjects with no AEFI, serving as controls. Two-hundred pre- and post-smallpox vaccination sera were analyzed by untargeted metabolomics using 1H nuclear magnetic resonance (NMR) spectroscopy. Baseline (pre-) and post-vaccination samples from individuals who experienced clinically verified myocarditis or asymptomatic elevation of troponins were more metabolically distinguishable pre- and post-vaccination compared to individuals who only experienced systemic symptoms, or controls. Metabolomics profiles pre- and post-receipt of vaccine differed substantially when an AEFI resulted. This study is the first to describe pre- and post-vaccination metabolic profiles of subjects who developed an adverse event following immunization. The study demonstrates the promise of metabolites for determining mechanisms associated with subjects who develop AEFI and the potential to develop predictive biomarkers. PMID:28169076

Metabolites as biomarkers of adverse reactions following vaccination: A pilot study using nuclear magnetic resonance metabolomics.

PubMed

McClenathan, Bruce M; Stewart, Delisha A; Spooner, Christina E; Pathmasiri, Wimal W; Burgess, Jason P; McRitchie, Susan L; Choi, Y Sammy; Sumner, Susan C J

2017-03-01

An Adverse Event Following Immunization (AEFI) is an adverse reaction to a vaccination that goes above and beyond the usual side effects associated with vaccinations. One serious AEFI related to the smallpox vaccine is myopericarditis. Metabolomics involves the study of the low molecular weight metabolite profile of cells, tissues, and biological fluids, and provides a functional readout of the phenotype. Metabolomics may help identify a particular metabolic signature in serum of subjects who are predisposed to developing AEFIs. The goal of this study was to identify metabolic markers that may predict the development of adverse events following smallpox vaccination. Serum samples were collected from military personnel prior to and following receipt of smallpox vaccine. The study population included five subjects who were clinically diagnosed with myopericarditis, 30 subjects with asymptomatic elevation of troponins, and 31 subjects with systemic symptoms following immunization, and 34 subjects with no AEFI, serving as controls. Two-hundred pre- and post-smallpox vaccination sera were analyzed by untargeted metabolomics using 1 H nuclear magnetic resonance (NMR) spectroscopy. Baseline (pre-) and post-vaccination samples from individuals who experienced clinically verified myocarditis or asymptomatic elevation of troponins were more metabolically distinguishable pre- and post-vaccination compared to individuals who only experienced systemic symptoms, or controls. Metabolomics profiles pre- and post-receipt of vaccine differed substantially when an AEFI resulted. This study is the first to describe pre- and post-vaccination metabolic profiles of subjects who developed an adverse event following immunization. The study demonstrates the promise of metabolites for determining mechanisms associated with subjects who develop AEFI and the potential to develop predictive biomarkers. Published by Elsevier Ltd.

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

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

Bag, Swarnendu, E-mail: Swarna.bag@gmail.com; Banerjee, Deb Ranjan, E-mail: debranjan2@gmail.com; Basak, Amit, E-mail: absk@chem.iitkgp.ernet.in

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.more » 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.« less

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

PubMed

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 Chromatography-Mass spectrometry.

Mass Spectrometry-Based Metabolomics to Elucidate Functions in Marine Organisms and Ecosystems

PubMed Central

Goulitquer, Sophie; Potin, Philippe; Tonon, Thierry

2012-01-01

Marine systems are very diverse and recognized as being sources of a wide range of biomolecules. This review provides an overview of metabolite profiling based on mass spectrometry (MS) approaches in marine organisms and their environments, focusing on recent advances in the field. We also point out some of the technical challenges that need to be overcome in order to increase applications of metabolomics in marine systems, including extraction of chemical compounds from different matrices and data management. Metabolites being important links between genotype and phenotype, we describe added value provided by integration of data from metabolite profiling with other layers of omics, as well as their importance for the development of systems biology approaches in marine systems to study several biological processes, and to analyze interactions between organisms within communities. The growing importance of MS-based metabolomics in chemical ecology studies in marine ecosystems is also illustrated. PMID:22690147

Emerging Applications of Metabolomic and Genomic Profiling in Diabetic Clinical Medicine

PubMed Central

McKillop, Aine M.; Flatt, Peter R.

2011-01-01

Clinical and epidemiological metabolomics provides a unique opportunity to look at genotype-phenotype relationships as well as the body\\x{2019}s responses to environmental and lifestyle factors. Fundamentally, it provides information on the universal outcome of influencing factors on disease states and has great potential in the early diagnosis, therapy monitoring, and understanding of the pathogenesis of disease. Diseases, such as diabetes, with a complex set of interactions between genetic and environmental factors, produce changes in the body\\x{2019}s biochemical profile, thereby providing potential markers for diagnosis and initiation of therapies. There is clearly a need to discover new ways to aid diagnosis and assessment of glycemic status to help reduce diabetes complications and improve the quality of life. Many factors, including peptides, proteins, metabolites, nucleic acids, and polymorphisms, have been proposed as putative biomarkers for diabetes. Metabolomics is an approach used to identify and assess metabolic characteristics, changes, and phenotypes in response to influencing factors, such as environment, diet, lifestyle, and pathophysiological states. The specificity and sensitivity using metabolomics to identify biomarkers of disease have become increasingly feasible because of advances in analytical and information technologies. Likewise, the emergence of high-throughput genotyping technologies and genome-wide association studies has prompted the search for genetic markers of diabetes predisposition or susceptibility. In this review, we consider the application of key metabolomic and genomic methodologies in diabetes and summarize the established, new, and emerging metabolomic and genomic biomarkers for the disease. We conclude by summarizing future insights into the search for improved biomarkers for diabetes research and human diagnostics. PMID:22110171

GC-TOF/MS-based metabolomic profiling of estrogen deficiency-induced obesity in ovariectomized rats

PubMed Central

Ma, Bo; Zhang, Qi; Wang, Guang-ji; A, Ji-ye; Wu, Di; Liu, Ying; Cao, Bei; Liu, Lin-sheng; Hu, Ying-ying; Wang, Yong-lu; Zheng, Ya-ya

2011-01-01

Aim: To explore the alteration of endogenous metabolites and identify potential biomarkers using metabolomic profiling with gas chromatography coupled a time-of-flight mass analyzer (GC/TOF-MS) in a rat model of estrogen-deficiency-induced obesity. Methods: Twelve female Sprague-Dawley rats six month of age were either sham-operated or ovariectomized (OVX). Rat blood was collected, and serum was analyzed for biomarkers using standard colorimetric methods with commercial assay kits and a metabolomic approach with GC/TOF-MS. The data were analyzed using multivariate statistical techniques. Results: A high body weight and body mass index inversely correlated with serum estradiol (E2) in the OVX rats compared to the sham rats. Estrogen deficiency also significantly increased serum total cholesterol, triglycerides, and low-density lipoprotein cholesterol. Utilizing GC/TOF-MS-based metabolomic analysis and the partial least-squares discriminant analysis, the OVX samples were discriminated from the shams. Elevated levels of cholesterol, glycerol, glucose, arachidonic acid, glutamic acid, glycine, and cystine and reduced alanine levels were observed. Serum glucose metabolism, energy metabolism, lipid metabolism, and amino acid metabolism were involved in estrogen-deficiency-induced obesity in OVX rats. Conclusion: The series of potential biomarkers identified in the present study provided fingerprints of rat metabolomic changes during obesity and an overview of multiple metabolic pathways during the progression of obesity involving glucose metabolism, lipid metabolism, and amino acid metabolism. PMID:21293480

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

PubMed

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

2016-11-01

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

Metabolomics - A wide-open door to personalized treatment in chronic heart failure?

PubMed

Marcinkiewicz-Siemion, M; Ciborowski, M; Kretowski, A; Musial, W J; Kaminski, K A

2016-09-15

Heart failure (HF) is a complex syndrome representing a final stage of various cardiovascular diseases. Despite significant improvement in the diagnosis and treatment (e.g. ACE-inhibitors, β-blockers, aldosterone antagonists, cardiac resynchronization therapy) of the disease, prognosis of optimally treated patients remains very serious and HF mortality is still unacceptably high. Therefore there is a strong need for further exploration of novel analytical methods, predictive and prognostic biomarkers and more personalized treatment. The metabolism of the failing heart being significantly impaired from its baseline state may be a future target not only for biomarker discovery but also for the pharmacologic intervention. However, an assessment of a particular, isolated metabolite or protein cannot be fully informative and makes a correct interpretation difficult. On the other hand, metabolites profile analysis may greatly assist investigator in an interpretation of the altered pathway dynamics, especially when combined with other lines of evidence (e.g. metabolites from the same pathway, transcriptomics, proteomics). Despite many prior studies on metabolism, the knowledge of peripheral and cardiac pathophysiological mechanisms responsible for the metabolic imbalance and progression of the disease is still insufficient. Metabolomics enabling comprehensive characterization of low molecular weight metabolites (e.g. lipids, sugars, organic acids, amino acids) that reflects the complete metabolic phenotype seems to be the key for further potential improvement in HF treatment (diet-based or biochemical-based). Will this -omics technique one day open a door to easy patients identification before they have a heart failure onset or its decompensation? Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Insulin resistance in prepubertal obese children correlates with sex-dependent early onset metabolomic alterations.

PubMed

Mastrangelo, A; Martos-Moreno, G Á; García, A; Barrios, V; Rupérez, F J; Chowen, J A; Barbas, C; Argente, J

2016-10-01

Insulin resistance (IR) is usually the first metabolic alteration diagnosed in obese children and the key risk factor for development of comorbidities. The factors determining whether or not IR develops as a result of excess body mass index (BMI) are still not completely understood. This study aimed to elucidate the mechanisms underpinning the predisposition toward hyperinsulinemia-related complications in obese children by using a metabolomic strategy that allows a profound interpretation of metabolic profiles potentially affected by IR. Serum from 60 prepubertal obese children (30 girls/30 boys, 50% IR and 50% non-IR in each group, but with similar BMIs) were analyzed by using liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry and capillary electrophoresis-mass spectrometry following an untargeted metabolomics approach. Validation was then performed on a group of 100 additional children with the same characteristics. When obese children with and without IR were compared, 47 metabolites out of 818 compounds (P<0.05) obtained after data pre-processing were found to be significantly different. Bile acids exhibit the greatest changes (that is, approximately a 90% increase in IR). The majority of metabolites differing between groups were lysophospholipids (15) and amino acids (17), indicating inflammation and central carbon metabolism as the most altered processes in impaired insulin signaling. Multivariate analysis (OPLS-DA models) showed subtle differences between groups that were magnified when females were analyzed alone. Inflammation and central carbon metabolism, together with the contribution of the gut microbiota, are the most altered processes in obese children with impaired insulin signaling in a sex-specific fashion despite their prepubertal status.

Diagnosis of gastroenterological diseases by metabolome analysis using gas chromatography-mass spectrometry.

PubMed

Yoshida, Masaru; Hatano, Naoya; Nishiumi, Shin; Irino, Yasuhiro; Izumi, Yoshihiro; Takenawa, Tadaomi; Azuma, Takeshi

2012-01-01

Recently, metabolome analysis has been increasingly applied to biomarker detection and disease diagnosis in medical studies. Metabolome analysis is a strategy for studying the characteristics and interactions of low molecular weight metabolites under a specific set of conditions and is performed using mass spectrometry and nuclear magnetic resonance spectroscopy. There is a strong possibility that changes in metabolite levels reflect the functional status of a cell because alterations in their levels occur downstream of DNA, RNA, and protein. Therefore, the metabolite profile of a cell is more likely to represent the current status of a cell than DNA, RNA, or protein. Thus, owing to the rapid development of mass spectrometry analytical techniques metabolome analysis is becoming an important experimental method in life sciences including the medical field. Here, we describe metabolome analysis using liquid chromatography-mass spectrometry, gas chromatography-mass spectrometry (GC-MS), capillary electrophoresis-mass spectrometry, and matrix assisted laser desorption ionization-mass spectrometry. Then, the findings of studies about GC-MS-based metabolome analysis of gastroenterological diseases are summarized, and our research results are also introduced. Finally, we discuss the realization of disease diagnosis by metabolome analysis. The development of metabolome analysis using mass spectrometry will aid the discovery of novel biomarkers, hopefully leading to the early detection of various diseases.

Capillary electrophoresis - Mass spectrometry metabolomics analysis revealed enrichment of hypotaurine in rat glioma tissues.

PubMed

Gao, Peng; Ji, Min; Fang, Xueyan; Liu, Yingyang; Yu, Zhigang; Cao, Yunfeng; Sun, Aijun; Zhao, Liang; Zhang, Yong

2017-11-15

Glioma is one of the most lethal brain malignancies with unknown etiologies. Many metabolomics analysis aiming at diverse kinds of samples had been performed. Due to the varied adopted analytical platforms, the reported disease-related metabolites were not consistent across different studies. Comparable metabolomics results are more likely to be acquired by analyzing the same sample types with identical analytical platform. For tumor researches, tissue samples metabolomics analysis own the unique advantage that it can gain more direct insight into disease-specific pathological molecules. In this light, a previous reported capillary electrophoresis - mass spectrometry human tissues metabolomics analysis method was employed to profile the metabolome of rat C6 cell implantation gliomas and the corresponding precancerous tissues. It was found that 9 metabolites increased in the glioma tissues. Of them, hypotaurine was the only metabolite that enriched in the malignant tissues as what had been reported in the relevant human tissues metabolomics analysis. Furthermore, hypotaurine was also proved to inhibit α-ketoglutarate-dependent dioxygenases (2-KDDs) through immunocytochemistry staining and in vitro enzymatic activity assays by using C6 cell cultures. This study reinforced the previous conclusion that hypotaurine acted as a competitive inhibitor of 2-KDDs and proved the value of metabolomics in oncology studies. Copyright © 2017. Published by Elsevier Inc.

Non-targeted plasma metabolomic profile at early and late lactation in parity 1 dams with diverging body composition at weaning

USDA-ARS?s Scientific Manuscript database

Lactation is an extremely energy demanding event, impacting naïve dams to a greater extent as they are still physiologically immature. The objective of the current study was to determine if a unique plasma metabolome exists at early and late lactation from first parity gilts having similar body meas...

Analysis of metabolomic profile of fermented Orostachys japonicus A. Berger by capillary electrophoresis time of flight mass spectrometry

PubMed Central

Das, Gitishree; Patra, Jayanta Kumar; Lee, Sun-Young; Kim, Changgeon; Park, Jae Gyu

2017-01-01

Microbial cell performance in food biotechnological processes has become an important concern for improving human health worldwide. Lactobacillus plantarum, which is widely distributed in nature, is a lactic acid bacterium with many industrial applications for fermented foods or functional foods (e.g., probiotics). In the present study, using capillary electrophoresis time of flight mass spectrometry, the metabolomic profile of dried Orostachys japonicus A. Berger, a perennial medicinal herb with L. plantarum was compared with that of O. japonicus fermented with L. plantarum to elucidate the metabolomic changes induced by the fermentation process. The levels of several metabolites were changed by the fermentation process, indicating their involvement in microbial performance. For example, glycolysis, the pentose phosphate pathway, the TCA cycle, the urea cycle-related metabolism, nucleotide metabolism, and lipid and amino acid metabolism were altered significantly by the fermentation process. Although the fermented metabolites were not tested using in vivo studies to increase human health benefits, our findings provide an insight into the alteration of metabolites induced by fermentation, and indicated that the metabolomic analysis for the process should be accompanied by fermenting strains and conditions. PMID:28704842

Analysis of metabolomic profile of fermented Orostachys japonicus A. Berger by capillary electrophoresis time of flight mass spectrometry.

PubMed

Das, Gitishree; Patra, Jayanta Kumar; Lee, Sun-Young; Kim, Changgeon; Park, Jae Gyu; Baek, Kwang-Hyun

2017-01-01

Microbial cell performance in food biotechnological processes has become an important concern for improving human health worldwide. Lactobacillus plantarum, which is widely distributed in nature, is a lactic acid bacterium with many industrial applications for fermented foods or functional foods (e.g., probiotics). In the present study, using capillary electrophoresis time of flight mass spectrometry, the metabolomic profile of dried Orostachys japonicus A. Berger, a perennial medicinal herb with L. plantarum was compared with that of O. japonicus fermented with L. plantarum to elucidate the metabolomic changes induced by the fermentation process. The levels of several metabolites were changed by the fermentation process, indicating their involvement in microbial performance. For example, glycolysis, the pentose phosphate pathway, the TCA cycle, the urea cycle-related metabolism, nucleotide metabolism, and lipid and amino acid metabolism were altered significantly by the fermentation process. Although the fermented metabolites were not tested using in vivo studies to increase human health benefits, our findings provide an insight into the alteration of metabolites induced by fermentation, and indicated that the metabolomic analysis for the process should be accompanied by fermenting strains and conditions.

Using fragmentation trees and mass spectral trees for identifying unknown compounds in metabolomics.

PubMed

Vaniya, Arpana; Fiehn, Oliver

2015-06-01

Identification of unknown metabolites is the bottleneck in advancing metabolomics, leaving interpretation of metabolomics results ambiguous. The chemical diversity of metabolism is vast, making structure identification arduous and time consuming. Currently, comprehensive analysis of mass spectra in metabolomics is limited to library matching, but tandem mass spectral libraries are small compared to the large number of compounds found in the biosphere, including xenobiotics. Resolving this bottleneck requires richer data acquisition and better computational tools. Multi-stage mass spectrometry (MSn) trees show promise to aid in this regard. Fragmentation trees explore the fragmentation process, generate fragmentation rules and aid in sub-structure identification, while mass spectral trees delineate the dependencies in multi-stage MS of collision-induced dissociations. This review covers advancements over the past 10 years as a tool for metabolite identification, including algorithms, software and databases used to build and to implement fragmentation trees and mass spectral annotations.

Fecal volatile organic compounds: a novel, cheaper method of diagnosing inflammatory bowel disease?

PubMed

Probert, Chris S J; Reade, Sophie; Ahmed, Iftikhar

2014-09-01

The investigation of a novel, cheaper method of diagnosing inflammatory bowel disease (IBD) is an area of active research. Recently, investigations into the metabolomic profile of IBD patients and animal models of colitis compared to healthy controls has begun to receive considerable attention and correlations between the fecal volatile organic compound (VOC) metabolome and IBD is merging. Patients and clinicians have often reported a change in odor of feces during relapse of IBD. Therefore, this article will focus specifically on the fecal VOC metabolome and its potential role in identifying a novel diagnostic method for IBD.

Comprehensive MS and Solid-State NMR Metabolomic Profiling Reveals Molecular Variations in Native Periderms from Four Solanum tuberosum Potato Cultivars.

PubMed

Huang, Wenlin; Serra, Olga; Dastmalchi, Keyvan; Jin, Liqing; Yang, Lijia; Stark, Ruth E

2017-03-15

The potato (Solanum tuberosum L.) ranks third in worldwide consumption among food crops. Whereas disposal of potato peels poses significant challenges for the food industry, secondary metabolites in these tissues are also bioactive and essential to crop development. The diverse primary and secondary metabolites reported in whole tubers and wound-healing tissues prompted a comprehensive profiling study of native periderms from four cultivars with distinctive skin morphologies and commercial food uses. Polar and nonpolar soluble metabolites were extracted concurrently, analyzed chromatographically, and characterized with mass spectrometry; the corresponding solid interfacial polymeric residue was examined by solid-state 13 C NMR. In total, 112 secondary metabolites were found in the phellem tissues; multivariate analysis identified 10 polar and 30 nonpolar potential biomarkers that distinguish a single cultivar among Norkotah Russet, Atlantic, Chipeta, and Yukon Gold cultivars which have contrasting russeting features. Compositional trends are interpreted in the context of periderm protective function.

Metabolic Disturbances in Adult-Onset Still's Disease Evaluated Using Liquid Chromatography/Mass Spectrometry-Based Metabolomic Analysis.

PubMed

Chen, Der-Yuan; Chen, Yi-Ming; Chien, Han-Ju; Lin, Chi-Chen; Hsieh, Chia-Wei; Chen, Hsin-Hua; Hung, Wei-Ting; Lai, Chien-Chen

2016-01-01

Liquid chromatography/mass spectrometry (LC/MS)-based comprehensive analysis of metabolic profiles with metabolomics approach has potential diagnostic and predictive implications. However, no metabolomics data have been reported in adult-onset Still's disease (AOSD). This study investigated the metabolomic profiles in AOSD patients and examined their association with clinical characteristics and disease outcome. Serum metabolite profiles were determined on 32 AOSD patients and 30 healthy controls (HC) using ultra-performance liquid chromatography (UPLC)/MS analysis, and the differentially expressed metabolites were quantified using multiple reactions monitoring (MRM)/MS analysis in 44 patients and 42 HC. Pure standards were utilized to confirm the presence of the differentially expressed metabolites. Eighteen differentially expressed metabolites were identified in AOSD patents using LC/MS-based analysis, of which 13 metabolites were validated by MRM/MS analysis. Among them, serum levels of lysoPC(18:2), urocanic acid and indole were significantly lower, and L-phenylalanine levels were significantly higher in AOSD patients compared with HC. Moreover, serum levels of lysoPC(18:2), PhePhe, uridine, taurine, L-threonine, and (R)-3-Hydroxy-hexadecanoic acid were significantly correlated with disease activity scores (all p<0.05) in AOSD patients. A different clustering of metabolites was associated with a different disease outcome, with significantly lower levels of isovalerylsarcosine observed in patients with chronic articular pattern (median, 77.0AU/ml) compared with monocyclic (341.5AU/ml, p<0.01) or polycyclic systemic pattern (168.0AU/ml, p<0.05). Thirteen differentially expressed metabolites identified and validated in AOSD patients were shown to be involved in five metabolic pathways. Significant associations of metabolic profiles with disease activity and outcome of AOSD suggest their involvement in AOSD pathogenesis.

Metabolomic analysis of urine with Nuclear Magnetic Resonance spectroscopy in patients with idiopathic sudden sensorineural hearing loss: A preliminary study.

PubMed

Carta, Filippo; Lussu, Milena; Bandino, Fabrizio; Noto, Antonio; Peppi, Marcello; Chuchueva, Natalia; Atzori, Luigi; Fanos, Vassilios; Puxeddu, Roberto

2017-08-01

Idiopathic sudden sensorineural hearing loss is a frequent emergency, with unknown aetiology and usually treated with empiric therapy. Steroids represent the only validated treatment but prognosis is unpredictable and the possibility to select the patients who will not respond to steroids could avoid unnecessary treatments. Metabolomic profiling of the biofluids target the analysis of the final product of genic expression and enzymatic activity, defining the biochemical phenotype of a whole biologic system. We studied the metabolomics of the urine of a cohort of patients with idiopathic sudden sensorineural hearing loss, correlating the metabolic profiles with the clinical outcomes. Metabolomic profiling of urine samples was performed by 1 H Nuclear Magnetic Resonance spectroscopy in combination with multivariate statistical approaches. 26 patients were included in the study: 5 healthy controls, 13 patients who did not recover after treatment at 6 months while the remaining 8 patients recovered from the hearing loss. The orthogonal partial least square-discriminant analysis score plot showed a significant separation between the two groups, responders and non-responders after steroid therapy, R 2 Y of 0.83, Q 2 of 0.38 and p value <0.05. The resulting metabolic profiles were characterized by higher levels of urinary B-Alanine, 3-hydroxybutyrate and Trimethylamine N-oxide, and lower levels of Citrate and Creatinine in patients with worst outcome. Idiopathic sudden sensorineural hearing loss is a specific disease with unclear systemic changes, but our data suggest that there are different types of this disorder or patients predisposed to effective action of steroids allowing the recover after treatment. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

Cortisol-related metabolic alterations assessed by mass spectrometry assay in patients with Cushing's syndrome.

PubMed

Di Dalmazi, Guido; Quinkler, Marcus; Deutschbein, Timo; Prehn, Cornelia; Rayes, Nada; Kroiss, Matthias; Berr, Christina M; Stalla, Günter; Fassnacht, Martin; Adamski, Jerzy; Reincke, Martin; Beuschlein, Felix

2017-08-01

Endogenous hypercortisolism is a chronic condition associated with severe metabolic disturbances and cardiovascular sequela. The aim of this study was to characterize metabolic alterations in patients with different degrees of hypercortisolism by mass-spectrometry-based targeted plasma metabolomic profiling and correlate the metabolomic profile with clinical and hormonal data. Cross-sectional study. Subjects ( n  = 149) were classified according to clinical and hormonal characteristics: Cushing's syndrome ( n  = 46), adrenocortical adenomas with autonomous cortisol secretion ( n  = 31) or without hypercortisolism ( n  = 27). Subjects with suspicion of hypercortisolism, but normal hormonal/imaging testing, served as controls ( n  = 42). Clinical and hormonal data were retrieved for all patients and targeted metabolomic profiling was performed. Patients with hypercortisolism showed lower levels of short-/medium-chain acylcarnitines and branched-chain and aromatic amino acids, but higher polyamines levels, in comparison to controls. These alterations were confirmed after excluding diabetic patients. Regression models showed significant correlation between cortisol after dexamethasone suppression test (DST) and 31 metabolites, independently of confounding/contributing factors. Among those, histidine and spermidine were also significantly associated with catabolic signs and symptoms of hypercortisolism. According to an discriminant analysis, the panel of metabolites was able to correctly classify subjects into the main diagnostic categories and to distinguish between subjects with/without altered post-DST cortisol and with/without diabetes in >80% of the cases. Metabolomic profiling revealed alterations of intermediate metabolism independently associated with the severity of hypercortisolism, consistent with disturbed protein synthesis/catabolism and incomplete β-oxidation, providing evidence for the occurrence of metabolic inflexibility in hypercortisolism. © 2017 European Society of Endocrinology.

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

PubMed Central

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

2014-01-01

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

Energy metabolic reprogramming in the hypertrophied and early stage failing heart: a multisystems approach.

PubMed

Lai, Ling; Leone, Teresa C; Keller, Mark P; Martin, Ola J; Broman, Aimee T; Nigro, Jessica; Kapoor, Kapil; Koves, Timothy R; Stevens, Robert; Ilkayeva, Olga R; Vega, Rick B; Attie, Alan D; Muoio, Deborah M; Kelly, Daniel P

2014-11-01

An unbiased systems approach was used to define energy metabolic events that occur during the pathological cardiac remodeling en route to heart failure (HF). Combined myocardial transcriptomic and metabolomic profiling were conducted in a well-defined mouse model of HF that allows comparative assessment of compensated and decompensated (HF) forms of cardiac hypertrophy because of pressure overload. The pressure overload data sets were also compared with the myocardial transcriptome and metabolome for an adaptive (physiological) form of cardiac hypertrophy because of endurance exercise training. Comparative analysis of the data sets led to the following conclusions: (1) expression of most genes involved in mitochondrial energy transduction were not significantly changed in the hypertrophied or failing heart, with the notable exception of a progressive downregulation of transcripts encoding proteins and enzymes involved in myocyte fatty acid transport and oxidation during the development of HF; (2) tissue metabolite profiles were more broadly regulated than corresponding metabolic gene regulatory changes, suggesting significant regulation at the post-transcriptional level; (3) metabolomic signatures distinguished pathological and physiological forms of cardiac hypertrophy and served as robust markers for the onset of HF; and (4) the pattern of metabolite derangements in the failing heart suggests bottlenecks of carbon substrate flux into the Krebs cycle. Mitochondrial energy metabolic derangements that occur during the early development of pressure overload-induced HF involve both transcriptional and post-transcriptional events. A subset of the myocardial metabolomic profile robustly distinguished pathological and physiological cardiac remodeling. © 2014 American Heart Association, Inc.

The Impact of Inflammation on Metabolomic Profiles in Patients With Arthritis

PubMed Central

Young, Stephen P; Kapoor, Sabrina R; Viant, Mark R; Byrne, Jonathan J; Filer, Andrew; Buckley, Christopher D; Kitas, George D; Raza, Karim

2013-01-01

Objective. Inflammatory arthritis is associated with systemic manifestations including alterations in metabolism. We used nuclear magnetic resonance (NMR) spectroscopy–based metabolomics to assess metabolic fingerprints in serum from patients with established rheumatoid arthritis (RA) and those with early arthritis. Methods. Serum samples were collected from newly presenting patients with established RA who were naive for disease-modifying antirheumatic drugs, matched healthy controls, and 2 groups of patients with synovitis of ≤3 months' duration whose outcomes were determined at clinical followup. Serum metabolomic profiles were assessed using 1-dimensional 1H-NMR spectroscopy. Discriminating metabolites were identified, and the relationships between metabolomic profiles and clinical variables including outcomes were examined. Results. The serum metabolic fingerprint in established RA was clearly distinct from that of healthy controls. In early arthritis, we were able to stratify the patients according to the level of current inflammation, with C-reactive protein correlating with metabolic differences in 2 separate groups (P < 0.001). Lactate and lipids were important discriminators of inflammatory burden in both early arthritis patient groups. The sensitivities and specificities of models to predict the development of either RA or persistent arthritis in patients with early arthritis were low. Conclusion. The metabolic fingerprint reflects inflammatory disease activity in patients with synovitis, demonstrating that underlying inflammatory processes drive significant changes in metabolism that can be measured in the peripheral blood. The identification of metabolic alterations may provide insights into disease mechanisms operating in patients with inflammatory arthritis. PMID:23740368

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

PubMed Central

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

2018-01-01

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

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

PubMed

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

2017-01-01

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

Metabolomic profiling and genomic analysis of wheat aneuploid lines to identify genes controlling biochemical pathways in mature grain.

PubMed

Francki, Michael G; Hayton, Sarah; Gummer, Joel P A; Rawlinson, Catherine; Trengove, Robert D

2016-02-01

Metabolomics is becoming an increasingly important tool in plant genomics to decipher the function of genes controlling biochemical pathways responsible for trait variation. Although theoretical models can integrate genes and metabolites for trait variation, biological networks require validation using appropriate experimental genetic systems. In this study, we applied an untargeted metabolite analysis to mature grain of wheat homoeologous group 3 ditelosomic lines, selected compounds that showed significant variation between wheat lines Chinese Spring and at least one ditelosomic line, tracked the genes encoding enzymes of their biochemical pathway using the wheat genome survey sequence and determined the genetic components underlying metabolite variation. A total of 412 analytes were resolved in the wheat grain metabolome, and principal component analysis indicated significant differences in metabolite profiles between Chinese Spring and each ditelosomic lines. The grain metabolome identified 55 compounds positively matched against a mass spectral library where the majority showed significant differences between Chinese Spring and at least one ditelosomic line. Trehalose and branched-chain amino acids were selected for detailed investigation, and it was expected that if genes encoding enzymes directly related to their biochemical pathways were located on homoeologous group 3 chromosomes, then corresponding ditelosomic lines would have a significant reduction in metabolites compared with Chinese Spring. Although a proportion showed a reduction, some lines showed significant increases in metabolites, indicating that genes directly and indirectly involved in biosynthetic pathways likely regulate the metabolome. Therefore, this study demonstrated that wheat aneuploid lines are suitable experimental genetic system to validate metabolomics-genomics networks. © 2015 Society for Experimental Biology, Association of Applied Biologists and John Wiley & Sons Ltd.

Integrated metabolomic profiling of hepatocellular carcinoma in hepatitis C cirrhosis through GC/MS and UPLC/MS-MS.

PubMed

Fitian, Asem I; Nelson, David R; Liu, Chen; Xu, Yiling; Ararat, Miguel; Cabrera, Roniel

2014-10-01

The metabolic pathway disturbances associated with hepatocellular carcinoma (HCC) remain unsatisfactorily characterized. Determination of the metabolic alterations associated with the presence of HCC can improve our understanding of the pathophysiology of this cancer and may provide opportunities for improved disease monitoring of patients at risk for HCC development. To characterize the global metabolic alterations associated with HCC arising from hepatitis C (HCV)-associated cirrhosis using an integrated non-targeted metabolomics methodology employing both gas chromatography/mass spectrometry (GC/MS) and ultrahigh-performance liquid chromatography/electrospray ionization tandem mass spectrometry (UPLC/MS-MS). The global serum metabolomes of 30 HCC patients, 27 hepatitis C cirrhosis disease controls and 30 healthy volunteers were characterized using a metabolomics approach that combined two metabolomics platforms, GC/MS and UPLC/MS-MS. Random forest, multivariate statistics and receiver operator characteristic analysis were performed to identify the most significantly altered metabolites in HCC patients vs. HCV-cirrhosis controls and which therefore exhibited a close association with the presence of HCC. Elevated 12-hydroxyeicosatetraenoic acid (12-HETE), 15-HETE, sphingosine, γ-glutamyl oxidative stress-associated metabolites, xanthine, amino acids serine, glycine and aspartate, and acylcarnitines were strongly associated with the presence of HCC. Elevations in bile acids and dicarboxylic acids were highly correlated with cirrhosis. Integrated metabolomic profiling through GC/MS and UPLC/MS-MS identified global metabolic disturbances in HCC and HCV-cirrhosis. Aberrant amino acid biosynthesis, cell turnover regulation, reactive oxygen species neutralization and eicosanoid pathways may be hallmarks of HCC. Aberrant dicarboxylic acid metabolism, enhanced bile acid metabolism and elevations in fibrinogen cleavage peptides may be signatures of cirrhosis. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Development and validation of a highly sensitive urine-based test to identify patients with colonic adenomatous polyps.

PubMed

Wang, Haili; Tso, Victor; Wong, Clarence; Sadowski, Dan; Fedorak, Richard N

2014-03-20

Adenomatous polyps are precursors of colorectal cancer; their detection and removal is the goal of colon cancer screening programs. However, fecal-based methods identify patients with adenomatous polyps with low levels of sensitivity. The aim or this study was to develop a highly accurate, prototypic, proof-of-concept, spot urine-based diagnostic test using metabolomic technology to distinguish persons with adenomatous polyps from those without polyps. Prospective urine and stool samples were collected from 876 participants undergoing colonoscopy examination in a colon cancer screening program, from April 2008 to October 2009 at the University of Alberta. Colonoscopy reference standard identified 633 participants with no colonic polyps and 243 with colonic adenomatous polyps. One-dimensional nuclear magnetic resonance spectra of urine metabolites were analyzed to define a diagnostic metabolomic profile for colonic adenomas. A urine metabolomic diagnostic test for colonic adenomatous polyps was established using 67% of the samples (un-blinded training set) and validated using the other 33% of the samples (blinded testing set). The urine metabolomic diagnostic test's specificity and sensitivity were compared with those of fecal-based tests. Using a two-component, orthogonal, partial least-squares model of the metabolomic profile, the un-blinded training set identified patients with colonic adenomatous polyps with 88.9% sensitivity and 50.2% specificity. Validation using the blinded testing set confirmed sensitivity and specificity values of 82.7% and 51.2%, respectively. Sensitivities of fecal-based tests to identify colonic adenomas ranged from 2.5 to 11.9%. We describe a proof-of-concept spot urine-based metabolomic diagnostic test that identifies patients with colonic adenomatous polyps with a greater level of sensitivity (83%) than fecal-based tests.

Metabolomic Profiling as a Possible Reverse Engineering Tool for Estimating Processing Conditions of Dry-Cured Hams.

PubMed

Sugimoto, Masahiro; Obiya, Shinichi; Kaneko, Miku; Enomoto, Ayame; Honma, Mayu; Wakayama, Masataka; Soga, Tomoyoshi; Tomita, Masaru

2017-01-18

Dry-cured hams are popular among consumers. To increase the attractiveness of the product, objective analytical methods and algorithms to evaluate the relationship between observable properties and consumer acceptability are required. In this study, metabolomics, which is used for quantitative profiling of hundreds of small molecules, was applied to 12 kinds of dry-cured hams from Japan and Europe. In total, 203 charged metabolites, including amino acids, organic acids, nucleotides, and peptides, were successfully identified and quantified. Metabolite profiles were compared for the samples with different countries of origin and processing methods (e.g., smoking or use of a starter culture). Principal component analysis of the metabolite profiles with sensory properties revealed significant correlations for redness, homogeneity, and fat whiteness. This approach could be used to design new ham products by objective evaluation of various features.

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

PubMed

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

2017-02-08

Universal acquisition of reliable information regarding the qualitative and quantitative properties of complicated matrices is the premise for the success of metabolomics study. Liquid chromatography-mass spectrometry (LC-MS) is now serving as a workhorse for metabolomics; however, LC-MS-based non-targeted metabolomics is suffering from some shortcomings, even some cutting-edge techniques have been introduced. Aiming to tackle, to some extent, the drawbacks of the conventional approaches, such as redundant information, detector saturation, low sensitivity, and inconstant signal number among different runs, herein, a novel and flexible work-flow consisting of three progressive steps was proposed to profile in depth the quantitative metabolome of plants. The roots of Peucedanum praeruptorum Dunn (Peucedani Radix, PR) that are rich in various coumarin isomers, were employed as a case study to verify the applicability. First, offline two dimensional LC-MS was utilized for in-depth detection of metabolites in a pooled PR extract namely universal metabolome standard (UMS). Second, mass fragmentation rules, notably concerning angular-type pyranocoumarins that are the primary chemical homologues in PR, and available databases were integrated for signal assignment and structural annotation. Third, optimum collision energy (OCE) as well as ion transition for multiple monitoring reaction measurement was online optimized with a reference compound-free strategy for each annotated component and large-scale relative quantification of all annotated components was accomplished by plotting calibration curves via serially diluting UMS. It is worthwhile to highlight that the potential of OCE for isomer discrimination was described and the linearity ranges of those primary ingredients were extended by suppressing their responses. The integrated workflow is expected to be qualified as a promising pipeline to clarify the quantitative metabolome of plants because it could not only holistically provide qualitative information, but also straightforwardly generate accurate quantitative dataset. Copyright © 2016 Elsevier B.V. All rights reserved.

Poplar trees reconfigure the transcriptome and metabolome in response to drought in a genotype- and time-of-day-dependent manner.

PubMed

Hamanishi, Erin T; Barchet, Genoa L H; Dauwe, Rebecca; Mansfield, Shawn D; Campbell, Malcolm M

2015-04-21

Drought has a major impact on tree growth and survival. Understanding tree responses to this stress can have important application in both conservation of forest health, and in production forestry. Trees of the genus Populus provide an excellent opportunity to explore the mechanistic underpinnings of forest tree drought responses, given the growing molecular resources that are available for this taxon. Here, foliar tissue of six water-deficit stressed P. balsamifera genotypes was analysed for variation in the metabolome in response to drought and time of day by using an untargeted metabolite profiling technique, gas chromatography/mass-spectrometry (GC/MS). Significant variation in the metabolome was observed in response the imposition of water-deficit stress. Notably, organic acid intermediates such as succinic and malic acid had lower concentrations in leaves exposed to drought, whereas galactinol and raffinose were found in increased concentrations. A number of metabolites with significant difference in accumulation under water-deficit conditions exhibited intraspecific variation in metabolite accumulation. Large magnitude fold-change accumulation was observed in three of the six genotypes. In order to understand the interaction between the transcriptome and metabolome, an integrated analysis of the drought-responsive transcriptome and the metabolome was performed. One P. balsamifera genotype, AP-1006, demonstrated a lack of congruence between the magnitude of the drought transcriptome response and the magnitude of the metabolome response. More specifically, metabolite profiles in AP-1006 demonstrated the smallest changes in response to water-deficit conditions. Pathway analysis of the transcriptome and metabolome revealed specific genotypic responses with respect to primary sugar accumulation, citric acid metabolism, and raffinose family oligosaccharide biosynthesis. The intraspecific variation in the molecular strategies that underpin the responses to drought among genotypes may have an important role in the maintenance of forest health and productivity.

Metabolomics in psoriatic disease: pilot study reveals metabolite differences in psoriasis and psoriatic arthritis

PubMed Central

Armstrong, April W.; Wu, Julie; Johnson, Mary Ann; Grapov, Dmitry; Azizi, Baktazh; Dhillon, Jaskaran; Fiehn, Oliver

2014-01-01

Importance: While “omics” studies have advanced our understanding of inflammatory skin diseases, metabolomics is mostly an unexplored field in dermatology. Objective: We sought to elucidate the pathogenesis of psoriatic diseases by determining the differences in metabolomic profiles among psoriasis patients with or without psoriatic arthritis and healthy controls. Design: We employed a global metabolomics approach to compare circulating metabolites from patients with psoriasis, psoriasis and psoriatic arthritis, and healthy controls. Setting: Study participants were recruited from the general community and from the Psoriasis Clinic at the University of California Davis in United States. Participants: We examined metabolomic profiles using blood serum samples from 30 patients age and gender matched into three groups: 10 patients with psoriasis, 10 patients with psoriasis and psoriatic arthritis and 10 control participants. Main outcome(s) and measures(s): Metabolite levels were measured calculating the mean peak intensities from gas chromatography time-of-flight mass spectrometry. Results: Multivariate analyses of metabolomics profiles revealed altered serum metabolites among the study population. Compared to control patients, psoriasis patients had a higher level of alpha ketoglutaric acid (Pso: 288 ± 88; Control: 209 ± 69; p=0.03), a lower level of asparagine (Pso: 5460 ± 980; Control: 7260 ± 2100; p=0.02), and a lower level of glutamine (Pso: 86000 ± 20000; Control: 111000 ± 27000; p=0.02). Compared to control patients, patients with psoriasis and psoriatic arthritis had increased levels of glucuronic acid (Pso + PsA: 638 ± 250; Control: 347 ± 61; p=0.001). Compared to patients with psoriasis alone, patients with both psoriasis and psoriatic arthritis had a decreased level of alpha ketoglutaric acid (Pso + PsA: 186 ± 80; Pso: 288 ± 88; p=0.02) and an increased level of lignoceric acid (Pso + PsA: 442 ± 280; Pso: 214 ± 64; p=0.02). Conclusions and relevance: The metabolite differences help elucidate the pathogenesis of psoriasis and psoriatic arthritis and they may provide insights for therapeutic development. PMID:25580230

Metabolome analysis of 20 taxonomically related benzylisoquinoline alkaloid-producing plants.

PubMed

Hagel, Jillian M; Mandal, Rupasri; Han, Beomsoo; Han, Jun; Dinsmore, Donald R; Borchers, Christoph H; Wishart, David S; Facchini, Peter J

2015-09-15

Recent progress toward the elucidation of benzylisoquinoline alkaloid (BIA) metabolism has focused on a small number of model plant species. Current understanding of BIA metabolism in plants such as opium poppy, which accumulates important pharmacological agents such as codeine and morphine, has relied on a combination of genomics and metabolomics to facilitate gene discovery. Metabolomics studies provide important insight into the primary biochemical networks underpinning specialized metabolism, and serve as a key resource for metabolic engineering, gene discovery, and elucidation of governing regulatory mechanisms. Beyond model plants, few broad-scope metabolomics reports are available for the vast number of plant species known to produce an estimated 2500 structurally diverse BIAs, many of which exhibit promising medicinal properties. We applied a multi-platform approach incorporating four different analytical methods to examine 20 non-model, BIA-accumulating plant species. Plants representing four families in the Ranunculales were chosen based on reported BIA content, taxonomic distribution and importance in modern/traditional medicine. One-dimensional (1)H NMR-based profiling quantified 91 metabolites and revealed significant species- and tissue-specific variation in sugar, amino acid and organic acid content. Mono- and disaccharide sugars were generally lower in roots and rhizomes compared with stems, and a variety of metabolites distinguished callus tissue from intact plant organs. Direct flow infusion tandem mass spectrometry provided a broad survey of 110 lipid derivatives including phosphatidylcholines and acylcarnitines, and high-performance liquid chromatography coupled with UV detection quantified 15 phenolic compounds including flavonoids, benzoic acid derivatives and hydroxycinnamic acids. Ultra-performance liquid chromatography coupled with high-resolution Fourier transform mass spectrometry generated extensive mass lists for all species, which were mined for metabolites putatively corresponding to BIAs. Different alkaloids profiles, including both ubiquitous and potentially rare compounds, were observed. Extensive metabolite profiling combining multiple analytical platforms enabled a more complete picture of overall metabolism occurring in selected plant species. This study represents the first time a metabolomics approach has been applied to most of these species, despite their importance in modern and traditional medicine. Coupled with genomics data, these metabolomics resources serve as a key resource for the investigation of BIA biosynthesis in non-model plant species.

Compound annotation in liquid chromatography/high-resolution mass spectrometry based metabolomics: robust adduct ion determination as a prerequisite to structure prediction in electrospray ionization mass spectra.

PubMed

Jaeger, Carsten; Méret, Michaël; Schmitt, Clemens A; Lisec, Jan

2017-08-15

A bottleneck in metabolic profiling of complex biological extracts is confident, non-supervised annotation of ideally all contained, chemically highly diverse small molecules. Recent computational strategies combining sum formula prediction with in silico fragmentation achieve confident de novo annotation, once the correct neutral mass of a compound is known. Current software solutions for automated adduct ion assignment, however, are either publicly unavailable or have been validated against only few experimental electrospray ionization (ESI) mass spectra. We here present findMAIN (find Main Adduct IoN), a new heuristic approach for interpreting ESI mass spectra. findMAIN scores MS 1 spectra based on explained intensity, mass accuracy and isotope charge agreement of adducts and related ionization products and annotates peaks of the (de)protonated molecule and adduct ions. The approach was validated against 1141 ESI positive mode spectra of chemically diverse standard compounds acquired on different high-resolution mass spectrometric instruments (Orbitrap and time-of-flight). Robustness against impure spectra was evaluated. Correct adduct ion assignment was achieved for up to 83% of the spectra. Performance was independent of compound class and mass spectrometric platform. The algorithm proved highly tolerant against spectral contamination as demonstrated exemplarily for co-eluting compounds as well as systematically by pairwise mixing of spectra. When used in conjunction with MS-FINDER, a state-of-the-art sum formula tool, correct sum formulas were obtained for 77% of spectra. It outperformed both 'brute force' approaches and current state-of-the-art annotation packages tested as potential alternatives. Limitations of the heuristic pertained to poorly ionizing compounds and cationic compounds forming [M] + ions. A new, validated approach for interpreting ESI mass spectra is presented, filling a gap in the nontargeted metabolomics workflow. It is freely available in the latest version of R package InterpretMSSpectrum. Copyright © 2017 John Wiley & Sons, Ltd.

Metabolomic and Transcriptomic Comparison of Solid-State and Submerged Fermentation of Penicillium expansum KACC 40815

PubMed Central

Park, Hye Min; Singh, Digar; Lee, Choong Hwan

2016-01-01

Penicillium spp. are known to harbor a wide array of secondary metabolites with cryptic bioactivities. However, the metabolomics of these species is not well-understood in terms of different fermentation models and conditions. The present study involved metabolomics profiling and transcriptomic analysis of Penicillium expansum 40815 under solid-state fermentation (SSF) and submerged fermentation (SmF). Metabolite profiling was carried out using ultra-performance liquid chromatography quadruple time-of-flight mass spectrometry with multivariate analysis, followed by transcriptomic analyses of differentially expressed genes. In principal component analysis, the metabolite profiling data was studied under different experimental sets, including SSF and SmF. The significantly different metabolites such as polyketide metabolites (agonodepside B, rotiorin, verrucosidin, and ochrephilone) and corresponding gene transcripts (polyketide synthase, aromatic prenyltransferase, and terpenoid synthase) were primarily detected under SmF conditions. In contrast, the meroterpenoid compounds (andrastin A and C) and their genes transcripts were exclusively detected under SSF conditions. We demonstrated that the metabolite production and its corresponding gene expression levels in P. expansum 40815 were significantly influenced by the varying growth parameters and the immediate environment. This study further provides a foundation to produce specific metabolites by regulating fermentation conditions. PMID:26863302

Urinary Metabolomic Approach Provides New Insights into Distinct Metabolic Profiles of Glutamine and N-Carbamylglutamate Supplementation in Rats.

PubMed

Liu, Guangmang; Cao, Wei; Fang, Tingting; Jia, Gang; Zhao, Hua; Chen, Xiaoling; Wu, Caimei; Wang, Jing

2016-08-04

Glutamine and N-carbamylglutamate can enhance growth performance and health in animals, but the underlying mechanisms are not yet elucidated. This study aimed to investigate the effect of glutamine and N-carbamylglutamate supplementation in rat metabolism. Thirty rats were fed a control, glutamine, or N-carbamylglutamate diet for four weeks. Urine samples were analyzed by nuclear magnetic resonance (NMR)-based metabolomics, specifically high-resolution ¹H NMR metabolic profiling combined with multivariate data analysis. Glutamine significantly increased the urine levels of acetamide, acetate, citrulline, creatinine, and methymalonate, and decreased the urine levels of ethanol and formate (p < 0.05). Moreover, N-carbamylglutamate significantly increased the urine levels of creatinine, ethanol, indoxyl sulfate, lactate, methymalonate, acetoacetate, m-hydroxyphenylacetate, and sarcosine, and decreased the urine levels of acetamide, acetate, citrulline, creatine, glycine, hippurate, homogentisate, N-acetylglutamate, phenylacetyglycine, acetone, and p-hydroxyphenylacetate (p < 0.05). Results suggested that glutamine and N-carbamylglutamate could modify urinary metabolome related to nitrogen metabolism and gut microbiota metabolism. Moreover, N-carbamylglutamate could alter energy and lipid metabolism. These findings indicate that different arginine precursors may lead to differences in the biofluid profile in rats.

Urinary Metabolomic Approach Provides New Insights into Distinct Metabolic Profiles of Glutamine and N-Carbamylglutamate Supplementation in Rats

PubMed Central

Liu, Guangmang; Cao, Wei; Fang, Tingting; Jia, Gang; Zhao, Hua; Chen, Xiaoling; Wu, Caimei; Wang, Jing

2016-01-01

Glutamine and N-carbamylglutamate can enhance growth performance and health in animals, but the underlying mechanisms are not yet elucidated. This study aimed to investigate the effect of glutamine and N-carbamylglutamate supplementation in rat metabolism. Thirty rats were fed a control, glutamine, or N-carbamylglutamate diet for four weeks. Urine samples were analyzed by nuclear magnetic resonance (NMR)-based metabolomics, specifically high-resolution 1H NMR metabolic profiling combined with multivariate data analysis. Glutamine significantly increased the urine levels of acetamide, acetate, citrulline, creatinine, and methymalonate, and decreased the urine levels of ethanol and formate (p < 0.05). Moreover, N-carbamylglutamate significantly increased the urine levels of creatinine, ethanol, indoxyl sulfate, lactate, methymalonate, acetoacetate, m-hydroxyphenylacetate, and sarcosine, and decreased the urine levels of acetamide, acetate, citrulline, creatine, glycine, hippurate, homogentisate, N-acetylglutamate, phenylacetyglycine, acetone, and p-hydroxyphenylacetate (p < 0.05). Results suggested that glutamine and N-carbamylglutamate could modify urinary metabolome related to nitrogen metabolism and gut microbiota metabolism. Moreover, N-carbamylglutamate could alter energy and lipid metabolism. These findings indicate that different arginine precursors may lead to differences in the biofluid profile in rats. PMID:27527211

Phytochemical diversity of cranberry (Vaccinium macrocarpon Aiton) cultivars by anthocyanin determination and metabolomic profiling with chemometric analysis.

PubMed

Brown, Paula N; Murch, Susan J; Shipley, Paul

2012-01-11

Originally native to the eastern United States, American cranberry ( Vaccinium macrocarpon Aiton, family Ericaceae) cultivation of native and hybrid varieties has spread across North America. Herein is reported the phytochemical diversity of five cranberry cultivars (Stevens, Ben Lear, Bergman, Pilgrim, and GH1) collected in the Greater Vancouver Regional District, by anthocyanin content and UPLC-TOF-MS metabolomic profiling. The anthocyanin content for biological replicates (n = 5) was determined as 7.98 ± 5.83, Ben Lear; 7.02 ± 1.75, Bergman; 6.05 ± 2.51, GH1; 3.28 ± 1.88, Pilgrim; and 2.81 ± 0.81, Stevens. Using subtractive metabonomic algorithms 6481 compounds were found conserved across all varietals, with 136 (Ben Lear), 84 (Bergman), 91 (GH1), 128 (Pilgrim), and 165 (Stevens) unique compounds observed. Principal component analysis (PCA) did not differentiate varieties, whereas partial least-squares discriminate analysis (PLS-DA) exhibited clustering patterns. Univariate statistical approaches were applied to the data set, establishing significance of values and assessing quality of the models. Metabolomic profiling with chemometric analysis proved to be useful for characterizing metabonomic changes across cranberry varieties.

Metabolomic profiling to identify potential serum biomarkers for schizophrenia and risperidone action.

PubMed

Xuan, Jiekun; Pan, Guihua; Qiu, Yunping; Yang, Lun; Su, Mingming; Liu, Yumin; Chen, Jian; Feng, Guoyin; Fang, Yiru; Jia, Wei; Xing, Qinghe; He, Lin

2011-12-02

Despite recent advances in understanding the pathophysiology of schizophrenia and the mechanisms of antipsychotic drug action, the development of biomarkers for diagnosis and therapeutic monitoring in schizophrenia remains challenging. Metabolomics provides a powerful approach to discover diagnostic and therapeutic biomarkers by analyzing global changes in an individual's metabolic profile in response to pathophysiological stimuli or drug intervention. In this study, we performed gas chromatography-mass spectrometry based metabolomic profiling in serum of unmedicated schizophrenic patients before and after an 8-week risperidone monotherapy, to detect potential biomarkers associated with schizophrenia and risperidone treatment. Twenty-two marker metabolites contributing to the complete separation of schizophrenic patients from matched healthy controls were identified, with citrate, palmitic acid, myo-inositol, and allantoin exhibiting the best combined classification performance. Twenty marker metabolites contributing to the complete separation between posttreatment and pretreatment patients were identified, with myo-inositol, uric acid, and tryptophan showing the maximum combined classification performance. Metabolic pathways including energy metabolism, antioxidant defense systems, neurotransmitter metabolism, fatty acid biosynthesis, and phospholipid metabolism were found to be disturbed in schizophrenic patients and partially normalized following risperidone therapy. Further study of these metabolites may facilitate the development of noninvasive biomarkers and more efficient therapeutic strategies for schizophrenia.

Metabolomic and Transcriptomic Comparison of Solid-State and Submerged Fermentation of Penicillium expansum KACC 40815.

PubMed

Kim, Hyang Yeon; Heo, Do Yeon; Park, Hye Min; Singh, Digar; Lee, Choong Hwan

2016-01-01

Penicillium spp. are known to harbor a wide array of secondary metabolites with cryptic bioactivities. However, the metabolomics of these species is not well-understood in terms of different fermentation models and conditions. The present study involved metabolomics profiling and transcriptomic analysis of Penicillium expansum 40815 under solid-state fermentation (SSF) and submerged fermentation (SmF). Metabolite profiling was carried out using ultra-performance liquid chromatography quadruple time-of-flight mass spectrometry with multivariate analysis, followed by transcriptomic analyses of differentially expressed genes. In principal component analysis, the metabolite profiling data was studied under different experimental sets, including SSF and SmF. The significantly different metabolites such as polyketide metabolites (agonodepside B, rotiorin, verrucosidin, and ochrephilone) and corresponding gene transcripts (polyketide synthase, aromatic prenyltransferase, and terpenoid synthase) were primarily detected under SmF conditions. In contrast, the meroterpenoid compounds (andrastin A and C) and their genes transcripts were exclusively detected under SSF conditions. We demonstrated that the metabolite production and its corresponding gene expression levels in P. expansum 40815 were significantly influenced by the varying growth parameters and the immediate environment. This study further provides a foundation to produce specific metabolites by regulating fermentation conditions.

Metabolomic profiling reveals deep chemical divergence between two morphotypes of the zoanthid Parazoanthus axinellae

NASA Astrophysics Data System (ADS)

Cachet, Nadja; Genta-Jouve, Grégory; Ivanisevic, Julijana; Chevaldonné, Pierre; Sinniger, Frédéric; Culioli, Gérald; Pérez, Thierry; Thomas, Olivier P.

2015-02-01

Metabolomics has recently proven its usefulness as complementary tool to traditional morphological and genetic analyses for the classification of marine invertebrates. Among the metabolite-rich cnidarian order Zoantharia, Parazoanthus is a polyphyletic genus whose systematics and phylogeny remain controversial. Within this genus, one of the most studied species, Parazoanthus axinellae is prominent in rocky shallow waters of the Mediterranean Sea and the NE Atlantic Ocean. Although different morphotypes can easily be distinguished, only one species is recognized to date. Here, a metabolomic profiling approach has been used to assess the chemical diversity of two main Mediterranean morphotypes, the ``slender'' and ``stocky'' forms of P. axinellae. Targeted profiling of their major secondary metabolites revealed a significant chemical divergence between the morphotypes. While zoanthoxanthin alkaloids and ecdysteroids are abundant in both morphs, the ``slender'' morphotype is characterized by the presence of additional and bioactive 3,5-disubstituted hydantoin derivatives named parazoanthines. The absence of these specific compounds in the ``stocky'' morphotype was confirmed by spatial and temporal monitoring over an annual cycle. Moreover, specimens of the ``slender'' morphotype are also the only ones found as epibionts of several sponge species, particularly Cymbaxinella damicornis thus suggesting a putative ecological link.

Metabolomic Analysis in Brain Research: Opportunities and Challenges

PubMed Central

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

2016-01-01

Metabolism being a fundamental part of molecular physiology, elucidating the structure and regulation of metabolic pathways is crucial for obtaining a comprehensive perspective of cellular function and understanding the underlying mechanisms of its dysfunction(s). Therefore, quantifying an accurate metabolic network activity map under various physiological conditions is among the major objectives of systems biology in the context of many biological applications. Especially for CNS, metabolic network activity analysis can substantially enhance our knowledge about the complex structure of the mammalian brain and the mechanisms of neurological disorders, leading to the design of effective therapeutic treatments. Metabolomics has emerged as the high-throughput quantitative analysis of the concentration profile of small molecular weight metabolites, which act as reactants and products in metabolic reactions and as regulatory molecules of proteins participating in many biological processes. Thus, the metabolic profile provides a metabolic activity fingerprint, through the simultaneous analysis of tens to hundreds of molecules of pathophysiological and pharmacological interest. The application of metabolomics is at its standardization phase in general, and the challenges for paving a standardized procedure are even more pronounced in brain studies. In this review, we support the value of metabolomics in brain research. Moreover, we demonstrate the challenges of designing and setting up a reliable brain metabolomic study, which, among other parameters, has to take into consideration the sex differentiation and the complexity of brain physiology manifested in its regional variation. We finally propose ways to overcome these challenges and design a study that produces reproducible and consistent results. PMID:27252656

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

PubMed Central

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

2016-01-01

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

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

PubMed

Wang, QuanQiu; Xu, Rong

2017-07-01

Human metabolomics has great potential in disease mechanism understanding, early diagnosis, and therapy. Existing metabolomics studies are often based on profiling patient biofluids and tissue samples and are difficult owing to the challenges of sample collection and data processing. Here, we report an alternative approach and developed a computation-based prediction system, MetabolitePredict, for disease metabolomics biomarker prediction. We applied MetabolitePredict to identify metabolite biomarkers and metabolite targeting therapies for rheumatoid arthritis (RA), a last-lasting complex disease with multiple genetic and environmental factors involved. MetabolitePredict is a de novo prediction system. It first constructs a disease-specific genetic profile using genes and pathways data associated with an input disease. It then constructs genetic profiles for a total of 259,170 chemicals/metabolites using known chemical genetics and human metabolomic data. MetabolitePredict prioritizes metabolites for a given disease based on the genetic profile similarities between disease and metabolites. We evaluated MetabolitePredict using 63 known RA-associated metabolites. MetabolitePredict found 24 of the 63 metabolites (recall: 0.38) and ranked them highly (mean ranking: top 4.13%, median ranking: top 1.10%, P-value: 5.08E-19). MetabolitePredict performed better than an existing metabolite prediction system, PROFANCY, in predicting RA-associated metabolites (PROFANCY: recall: 0.31, mean ranking: 20.91%, median ranking: 16.47%, P-value: 3.78E-7). Short-chain fatty acids (SCFAs), the abundant metabolites of gut microbiota in the fermentation of fiber, ranked highly (butyrate, 0.03%; acetate, 0.05%; propionate, 0.38%). Finally, we established MetabolitePredict's potential in novel metabolite targeting for disease treatment: MetabolitePredict ranked highly three known metabolite inhibitors for RA treatments (methotrexate:0.25%; leflunomide: 0.56%; sulfasalazine: 0.92%). MetabolitePredict is a generalizable disease metabolite prediction system. The only required input to the system is a disease name or a set of disease-associated genes. The web-based MetabolitePredict is available at:http://xulab. edu/MetabolitePredict. Copyright © 2017 Elsevier Inc. All rights reserved.

Vitamin D prenatal programming of childhood metabolomics profiles at age 3 y.

PubMed

Blighe, Kevin; Chawes, Bo L; Kelly, Rachel S; Mirzakhani, Hooman; McGeachie, Michael; Litonjua, Augusto A; Weiss, Scott T; Lasky-Su, Jessica A

2017-10-01

Background: Vitamin D deficiency is implicated in a range of common complex diseases that may be prevented by gestational vitamin D repletion. Understanding the metabolic mechanisms related to in utero vitamin D exposure may therefore shed light on complex disease susceptibility. Objective: The goal was to analyze the programming role of in utero vitamin D exposure on children's metabolomics profiles. Design: First, unsupervised clustering was done with plasma metabolomics profiles from a case-control subset of 245 children aged 3 y with and without asthma from the Vitamin D Antenatal Asthma Reduction Trial (VDAART), in which pregnant women were randomly assigned to vitamin D supplementation or placebo. Thereafter, we analyzed the influence of maternal pre- and postsupplement vitamin D concentrations on cluster membership. Finally, we used the metabolites driving the clustering of children to identify the dominant metabolic pathways that were influential in each cluster. Results: We identified 3 clusters of children characterized by 1 ) high concentrations of fatty acids and amines and low maternal postsupplement vitamin D (mean ± SD; 27.5 ± 11.0 ng/mL), 2 ) high concentrations of amines, moderate concentrations of fatty acids, and normal maternal postsupplement vitamin D (34.0 ± 14.1 ng/mL), and 3 ) low concentrations of fatty acids, amines, and normal maternal postsupplement vitamin D (35.2 ± 15.9 ng/mL). Adjusting for sample storage time, maternal age and education, and both child asthma and vitamin D concentration at age 3 y did not modify the association between maternal postsupplement vitamin D and cluster membership ( P = 0.0014). Maternal presupplement vitamin D did not influence cluster membership, whereas the combination of pre- and postsupplement concentrations did ( P = 0.03). Conclusions: Young children can be clustered into distinct biologically meaningful groups by their metabolomics profiles. The clusters differed in concentrations of inflammatory mediators, and cluster membership was influenced by in utero vitamin D exposure, suggesting a prenatal programming role of vitamin D on the child's metabolome. This trial was registered at clinicaltrials.gov as NCT00920621. © 2017 American Society for Nutrition.

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

PubMed

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

2016-01-07

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

Glucose enhances tilapia against Edwardsiella tarda infection through metabolome reprogramming.

PubMed

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

2017-02-01

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

Quantification of Microbial Phenotypes

PubMed Central

Martínez, Verónica S.; Krömer, Jens O.

2016-01-01

Metabolite profiling technologies have improved to generate close to quantitative metabolomics data, which can be employed to quantitatively describe the metabolic phenotype of an organism. Here, we review the current technologies available for quantitative metabolomics, present their advantages and drawbacks, and the current challenges to generate fully quantitative metabolomics data. Metabolomics data can be integrated into metabolic networks using thermodynamic principles to constrain the directionality of reactions. Here we explain how to estimate Gibbs energy under physiological conditions, including examples of the estimations, and the different methods for thermodynamics-based network analysis. The fundamentals of the methods and how to perform the analyses are described. Finally, an example applying quantitative metabolomics to a yeast model by 13C fluxomics and thermodynamics-based network analysis is presented. The example shows that (1) these two methods are complementary to each other; and (2) there is a need to take into account Gibbs energy errors. Better estimations of metabolic phenotypes will be obtained when further constraints are included in the analysis. PMID:27941694

Single-cell metabolomics: analytical and biological perspectives.

PubMed

Zenobi, R

2013-12-06

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

Impact of Intestinal Microbiota on Intestinal Luminal Metabolome

PubMed Central

Matsumoto, Mitsuharu; Kibe, Ryoko; Ooga, Takushi; Aiba, Yuji; Kurihara, Shin; Sawaki, Emiko; Koga, Yasuhiro; Benno, Yoshimi

2012-01-01

Low–molecular-weight metabolites produced by intestinal microbiota play a direct role in health and disease. In this study, we analyzed the colonic luminal metabolome using capillary electrophoresis mass spectrometry with time-of-flight (CE-TOFMS) —a novel technique for analyzing and differentially displaying metabolic profiles— in order to clarify the metabolite profiles in the intestinal lumen. CE-TOFMS identified 179 metabolites from the colonic luminal metabolome and 48 metabolites were present in significantly higher concentrations and/or incidence in the germ-free (GF) mice than in the Ex-GF mice (p < 0.05), 77 metabolites were present in significantly lower concentrations and/or incidence in the GF mice than in the Ex-GF mice (p < 0.05), and 56 metabolites showed no differences in the concentration or incidence between GF and Ex-GF mice. These indicate that intestinal microbiota highly influenced the colonic luminal metabolome and a comprehensive understanding of intestinal luminal metabolome is critical for clarifying host-intestinal bacterial interactions. PMID:22724057

Characterization of proteomic and metabolomic responses to dietary factors and supplements.

PubMed

Astle, John; Ferguson, Jonathan T; German, J Bruce; Harrigan, George G; Kelleher, Neil L; Kodadek, Thomas; Parks, Bryan A; Roth, Michael J; Singletary, Keith W; Wenger, Craig D; Mahady, Gail B

2007-12-01

Over the past decade there has been a renewed interest in research and development of both dietary and nutritional supplements. Significant advancements have been made in the scientific assessment of the quality, safety, and efficacy of these products because of the strong interest in and financial support of these projects. As research in both fields continues to advance, opportunities to use new and innovative research technologies and methodologies, such as proteomics and metabolomics, are critical for the future progress of the science. The purpose of the symposium was to begin the process of communicating new innovative proteomic and metabolomic methodologies that may be applied by researchers in both the nutrition and the natural product communities. This symposium highlighted 2 proteomic approaches, protein fingerprinting in complex mixtures with peptoid microarrays and top-down mass spectrometry for annotation of gene products. Likewise, an overview of the methodologies used in metabolomic profiling of natural products was presented, and an illustration of an integrated metabolomics approach in nutrition research was highlighted.

Reprogramming the metabolome rescues retinal degeneration.

PubMed

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

2018-05-01

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

GC/MS-based metabolomic studies reveal key roles of glycine in regulating silk synthesis in silkworm, Bombyx mori.

PubMed

Chen, Quanmei; Liu, Xinyu; Zhao, Ping; Sun, Yanhui; Zhao, Xinjie; Xiong, Ying; Xu, Guowang; Xia, Qingyou

2015-02-01

Metabolic profiling of silkworm, especially the factors that affect silk synthesis at the metabolic level, is little known. Herein, metabolomic method based on gas chromatography-mass spectrometry was applied to identify key metabolic changes in silk synthesis deficient silkworms. Forty-six differential metabolites were identified in Nd group with the defect of silk synthesis. Significant changes in the levels of glycine and uric acid (up-regulation), carbohydrates and free fatty acids (down-regulation) were observed. The further metabolomics of silk synthesis deficient silkworms by decreasing silk proteins synthesis using knocking out fibroin heavy chain gene or extirpating silk glands operation showed that the changes of the metabolites were almost consistent with those of the Nd group. Furthermore, the increased silk yields by supplying more glycine or its related metabolite confirmed that glycine is a key metabolite to regulate silk synthesis. These findings provide important insights into the regulation between metabolic profiling and silk synthesis. Copyright © 2014 Elsevier Ltd. All rights reserved.

High-resolution metabolic mapping of cell types in plant roots

PubMed Central

Moussaieff, Arieh; Rogachev, Ilana; Brodsky, Leonid; Malitsky, Sergey; Toal, Ted W.; Belcher, Heather; Yativ, Merav; Brady, Siobhan M.; Benfey, Philip N.; Aharoni, Asaph

2013-01-01

Metabolite composition offers a powerful tool for understanding gene function and regulatory processes. However, metabolomics studies on multicellular organisms have thus far been performed primarily on whole organisms, organs, or cell lines, losing information about individual cell types within a tissue. With the goal of profiling metabolite content in different cell populations within an organ, we used FACS to dissect GFP-marked cells from Arabidopsis roots for metabolomics analysis. Here, we present the metabolic profiles obtained from five GFP-tagged lines representing core cell types in the root. Fifty metabolites were putatively identified, with the most prominent groups being glucosinolates, phenylpropanoids, and dipeptides, the latter of which is not yet explored in roots. The mRNA expression of enzymes or regulators in the corresponding biosynthetic pathways was compared with the relative metabolite abundance. Positive correlations suggest that the rate-limiting steps in biosynthesis of glucosinolates in the root are oxidative modifications of side chains. The current study presents a work flow for metabolomics analyses of cell-type populations. PMID:23476065

Urine metabolomics.

PubMed

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

2012-12-24

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

1H NMR-metabolomics: can they be a useful tool in our understanding of cardiac arrest?

PubMed

Chalkias, Athanasios; Fanos, Vassilios; Noto, Antonio; Castrén, Maaret; Gulati, Anil; Svavarsdóttir, Hildigunnur; Iacovidou, Nicoletta; Xanthos, Theodoros

2014-05-01

This review focuses on the presentation of the emerging technology of metabolomics, a promising tool for the detection of identifying the unrevealed biological pathways that lead to cardiac arrest. The electronic bases of PubMed, Scopus, and EMBASE were searched. Research terms were identified using the MESH database and were combined thereafter. Initial search terms were "cardiac arrest", "cardiopulmonary resuscitation", "post-cardiac arrest syndrome" combined with "metabolomics". Metabolomics allow the monitoring of hundreds of metabolites from tissues or body fluids and already influence research in the field of cardiac metabolism. This approach has elucidated several pathophysiological mechanisms and identified profiles of metabolic changes that can be used to follow the disease processes occurring in the peri-arrest period. This can be achieved through leveraging the strengths of unbiased metabolome-wide scans, which include thousands of final downstream products of gene transcription, enzyme activity and metabolic products of extraneously administered substances, in order to identify a metabolomic fingerprint associated with an increased risk of cardiac arrest. Although this technology is still under development, metabolomics is a promising tool for elucidating biological pathways and discovering clinical biomarkers, strengthening the efforts for optimizing both the prevention and treatment of cardiac arrest. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

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

2017-07-07

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

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

PubMed Central

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

Cardioprotective and Metabolomic Profiling of Selected Medicinal Plants against Oxidative Stress

PubMed Central

Afsheen, Nadia; Jahan, Nazish; Ijaz, Misbah; Manzoor, Asad; Khan, Khalid Mahmood; Hina, Saman

2018-01-01

In this research work, the antioxidant and metabolomic profiling of seven selected medicinally important herbs including Rauvolfia serpentina, Terminalia arjuna, Coriandrum sativum, Elettaria cardamom, Piper nigrum, Allium sativum, and Crataegus oxyacantha was performed. The in vivo cardioprotective potential of these medicinal plants was evaluated against surgically induced oxidative stress through left anterior descending coronary artery ligation (LADCA) in dogs. The antioxidant profiling of these plants was done through DPPH and DNA protection assay. The C. oxyacantha and T. arjuna showed maximum antioxidant potential, while the E. cardamom showed poor antioxidative strength even at its high concentration. Different concentrations of extracts of the said plants exhibited the protection of plasmid DNA against H2O2 damage as compared to the plasmid DNA merely treated with H2O2. The metabolomic profiling through LC-MS analysis of these antioxidants revealed the presence of active secondary metabolites responsible for their antioxidant potential. During in vivo analysis, blood samples of all treatment groups were drawn at different time intervals to analyze the cardiac and hemodynamic parameters. The results depicted that the group pretreated with HC4 significantly sustained the level of CK-MB, SGOT, and LDH as well as hemodynamic parameters near to normal. The histopathological examination also confirmed the cardioprotective potential of HC4. Thus, the HC4 being safe and inexpensive cardioprotective herbal combination could be considered as an alternate of synthetic drugs. PMID:29576858

Metabolomic assessment of key maize resources: GC-MS and NMR profiling of grain from B73 hybrids of the nested association mapping (NAM) founders and of geographically diverse landraces

USDA-ARS?s Scientific Manuscript database

The present study expands metabolomic assessments of maize beyond commercial elite lines to include two sets of publicly available lines used extensively in the scientific community to investigate the genetic basis of complex plant traits or that may serve as a source of new alleles for improving mo...

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

PubMed Central

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

2006-01-01

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

Nuclear Magnetic Resonance metabolomics reveals an excretory metabolic signature of renal cell carcinoma.

PubMed

Monteiro, Márcia S; Barros, António S; Pinto, Joana; Carvalho, Márcia; Pires-Luís, Ana S; Henrique, Rui; Jerónimo, Carmen; Bastos, Maria de Lourdes; Gil, Ana M; Guedes de Pinho, Paula

2016-11-18

RCC usually develops and progresses asymptomatically and, when detected, it is frequently at advanced stages and metastatic, entailing a dismal prognosis. Therefore, there is an obvious demand for new strategies enabling an earlier diagnosis. The importance of metabolic rearrangements for carcinogenesis unlocked a new approach for cancer research, catalyzing the increased use of metabolomics. The present study aimed the NMR metabolic profiling of RCC in urine samples from a cohort of RCC patients (n = 42) and controls (n = 49). The methodology entailed variable selection of the spectra in tandem with multivariate analysis and validation procedures. The retrieval of a disease signature was preceded by a systematic evaluation of the impacts of subject age, gender, BMI, and smoking habits. The impact of confounders on the urine metabolomics profile of this population is residual compared to that of RCC. A 32-metabolite/resonance signature descriptive of RCC was unveiled, successfully distinguishing RCC patients from controls in principal component analysis. This work demonstrates the value of a systematic metabolomics workflow for the identification of robust urinary metabolic biomarkers of RCC. Future studies should entail the validation of the 32-metabolite/resonance signature found for RCC in independent cohorts, as well as biological validation of the putative hypotheses advanced.

Capturing the metabolomic diversity of KRAS mutants in non-small-cell lung cancer cells

PubMed Central

Marabese, Mirko; Broggini, Massimo; Pastorelli, Roberta

2014-01-01

In non-small-cell lung cancer (NSCLC), one-fifth of patients have KRAS mutations, which are considered a negative predictive factor to first-line therapy. Evidence is emerging that not all KRAS mutations have the same biological activities and possible remodeling of cell metabolism by KRAS activation might complicate the scenario. An open question is whether different KRAS mutations at codon-12 affect cellular metabolism differently with possible implications for different responses to cancer treatments. We applied an explorative mass spectrometry-based untargeted metabolomics strategy to characterize the largest possible number of metabolites that might distinguish isogenic NSCLC cells overexpressing mutated forms of KRAS at codon-12 (G12C, G12D, G12V) and the wild-type. The glutamine deprivation assay and real-time PCR were used to confirm the involvement of some of the metabolic pathways highlighted. Cell clones indicated distinct metabolomic profiles in KRAS wild-type and mutants. Clones harboring different KRAS mutations at codon-12 also had different metabolic remodeling, such as a different redox buffering system and different glutamine-dependency not driven by the transcriptional state of enzymes involved in glutaminolysis. These findings indicate that KRAS mutations at codon-12 are associated with different metabolomic profiles that might affect the responses to cancer treatments. PMID:24952473

A Combined Metabolomic and Proteomic Analysis of Gestational Diabetes Mellitus

PubMed Central

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

2015-01-01

The aim of this pilot study was to apply a novel combined metabolomic and proteomic approach in analysis of gestational diabetes mellitus. The investigation was performed with plasma samples derived from pregnant women with diagnosed gestational diabetes mellitus (n = 18) and a matched control group (n = 13). The mass spectrometry-based analyses allowed to determine 42 free amino acids and low molecular-weight peptide profiles. Different expressions of several peptides and altered amino acid profiles were observed in the analyzed groups. The combination of proteomic and metabolomic data allowed obtaining the model with a high discriminatory power, where amino acids ethanolamine, l-citrulline, l-asparagine, and peptide ions with m/z 1488.59; 4111.89 and 2913.15 had the highest contribution to the model. The sensitivity (94.44%) and specificity (84.62%), as well as the total group membership classification value (90.32%) calculated from the post hoc classification matrix of a joint model were the highest when compared with a single analysis of either amino acid levels or peptide ion intensities. The obtained results indicated a high potential of integration of proteomic and metabolomics analysis regardless the sample size. This promising approach together with clinical evaluation of the subjects can also be used in the study of other diseases. PMID:26694367

Metabolomic signature associated with reproduction-regulated aging in Caenorhabditis elegans.

PubMed

Wan, Qin-Li; Shi, Xiaohuo; Liu, Jiangxin; Ding, Ai-Jun; Pu, Yuan-Zhu; Li, Zhigang; Wu, Gui-Sheng; Luo, Huai-Rong

2017-02-06

In Caenorhabditis elegans (C. elegans) , ablation of germline stem cells (GSCs) leads to infertility, which extends lifespan. It has been reported that aging and reproduction are both inextricably associated with metabolism. However, few studies have investigated the roles of polar small molecules metabolism in regulating longevity by reproduction. In this work, we combined the nuclear magnetic resonance (NMR) and ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) to profile the water-soluble metabolome in C. elegans . Comparing the metabolic fingerprint between two physiological ages among different mutants, our results demonstrate that aging is characterized by metabolome remodeling and metabolic decline. In addition, by analyzing the metabolic profiles of long-lived germline-less glp-1 mutants, we discovered that glp-1 mutants regulate the levels of many age-variant metabolites to attenuate aging, including elevated concentrations of the pyrimidine and purine metabolism intermediates and decreased concentrations of the citric acid cycle intermediates. Interestingly, by analyzing the metabolome of daf-16;glp-1 double mutants, our results revealed that some metabolic exchange contributing to germline-mediated longevity was mediated by transcription factor FOXO/DAF-16, including pyrimidine metabolism and the TCA cycle. Based on a comprehensive metabolic analysis, we provide novel insight into the relationship between longevity and metabolism regulated by germline signals in C. elegans .

Metabolomic signature associated with reproduction-regulated aging in Caenorhabditis elegans

PubMed Central

Wan, Qin-Li; Shi, Xiaohuo; Liu, Jiangxin; Ding, Ai-Jun; Pu, Yuan-Zhu; Li, Zhigang; Wu, Gui-Sheng; Luo, Huai-Rong

2017-01-01

In Caenorhabditis elegans (C. elegans), ablation of germline stem cells (GSCs) leads to infertility, which extends lifespan. It has been reported that aging and reproduction are both inextricably associated with metabolism. However, few studies have investigated the roles of polar small molecules metabolism in regulating longevity by reproduction. In this work, we combined the nuclear magnetic resonance (NMR) and ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) to profile the water-soluble metabolome in C. elegans. Comparing the metabolic fingerprint between two physiological ages among different mutants, our results demonstrate that aging is characterized by metabolome remodeling and metabolic decline. In addition, by analyzing the metabolic profiles of long-lived germline-less glp-1 mutants, we discovered that glp-1 mutants regulate the levels of many age-variant metabolites to attenuate aging, including elevated concentrations of the pyrimidine and purine metabolism intermediates and decreased concentrations of the citric acid cycle intermediates. Interestingly, by analyzing the metabolome of daf-16;glp-1 double mutants, our results revealed that some metabolic exchange contributing to germline-mediated longevity was mediated by transcription factor FOXO/DAF-16, including pyrimidine metabolism and the TCA cycle. Based on a comprehensive metabolic analysis, we provide novel insight into the relationship between longevity and metabolism regulated by germline signals in C. elegans PMID:28177875

LC-MS based metabolomics and chemometrics study of the toxic effects of copper on Saccharomyces cerevisiae.

PubMed

Farrés, Mireia; Piña, Benjamí; Tauler, Romà

2016-08-01

Copper containing fungicides are used to protect vineyards from fungal infections. Higher residues of copper in grapes at toxic concentrations are potentially toxic and affect the microorganisms living in vineyards, such as Saccharomyces cerevisiae. In this study, the response of the metabolic profiles of S. cerevisiae at different concentrations of copper sulphate (control, 1 mM, 3 mM and 6 mM) was analysed by liquid chromatography coupled to mass spectrometry (LC-MS) and multivariate curve resolution-alternating least squares (MCR-ALS) using an untargeted metabolomics approach. Peak areas of the MCR-ALS resolved elution profiles in control and in Cu(ii)-treated samples were compared using partial least squares regression (PLSR) and PLS-discriminant analysis (PLS-DA), and the intracellular metabolites best contributing to sample discrimination were selected and identified. Fourteen metabolites showed significant concentration changes upon Cu(ii) exposure, following a dose-response effect. The observed changes were consistent with the expected effects of Cu(ii) toxicity, including oxidative stress and DNA damage. This research confirmed that LC-MS based metabolomics coupled to chemometric methods are a powerful approach for discerning metabolomics changes in S. cerevisiae and for elucidating modes of toxicity of environmental stressors, including heavy metals like Cu(ii).

Metabolomic Profiles of Current Cigarette Smokers

PubMed Central

Hsu, Ping-Ching; Lan, Renny S.; Brasky, Theodore M.; Marian, Catalin; Cheema, Amrita K.; Ressom, Habtom W.; Loffredo, Christopher A.; Pickworth, Wallace B.; Shields, Peter G.

2017-01-01

Smoking-related biomarkers for lung cancer and other diseases are needed to enhance early detection strategies and to provide a science base for tobacco product regulation. An untargeted metabolomics approach by ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry (UHPLC-Q-TOF MS) totaling 957 assays was used in a novel experimental design where 105 current smokers smoked 2 cigarettes one hour apart. Blood was collected immediately before and after each cigarette allowing for within-subject replication. Dynamic changes of the metabolomic profiles from smokers’ four blood samples were observed and biomarkers affected by cigarette smoking were identified. Thirty-one metabolites were definitively shown to be affected by acute effect of cigarette smoking, uniquely including menthol-glucuronide, the reduction of glutamate, oleamide, and 13 glycerophospholipids. This first time identification of a menthol metabolite in smokers’ blood serves as proof-of-principle for using metabolomics to identify new tobacco-exposure biomarkers, and also provides new opportunities in studying menthol-containing tobacco products in humans. Gender and race differences also were observed. Network analysis revealed 12 molecules involved in cancer, notably inhibition of cAMP. These novel tobacco-related biomarkers provide new insights to the effects of smoking which may be important in carcinogenesis but not previously linked with tobacco-related diseases. PMID:27341184

Mapping an atlas of tissue-specific Drosophila melanogaster metabolomes by high resolution mass spectrometry.

PubMed

Chintapalli, Venkateswara R; Al Bratty, Mohammed; Korzekwa, Dominika; Watson, David G; Dow, Julian A T

2013-01-01

Metabolomics can provide exciting insights into organismal function, but most work on simple models has focussed on the whole organism metabolome, so missing the contributions of individual tissues. Comprehensive metabolite profiles for ten tissues from adult Drosophila melanogaster were obtained here by two chromatographic methods, a hydrophilic interaction (HILIC) method for polar metabolites and a lipid profiling method also based on HILIC, in combination with an Orbitrap Exactive instrument. Two hundred and forty two polar metabolites were putatively identified in the various tissues, and 251 lipids were observed in positive ion mode and 61 in negative ion mode. Although many metabolites were detected in all tissues, every tissue showed characteristically abundant metabolites which could be rationalised against specific tissue functions. For example, the cuticle contained high levels of glutathione, reflecting a role in oxidative defence; the alimentary canal (like vertebrate gut) had high levels of acylcarnitines for fatty acid metabolism, and the head contained high levels of ether lipids. The male accessory gland uniquely contained decarboxylated S-adenosylmethionine. These data thus both provide valuable insights into tissue function, and a reference baseline, compatible with the FlyAtlas.org transcriptomic resource, for further metabolomic analysis of this important model organism, for example in the modelling of human inborn errors of metabolism, aging or metabolic imbalances such as diabetes.

Deep Learning Accurately Predicts Estrogen Receptor Status in Breast Cancer Metabolomics Data.

PubMed

Alakwaa, Fadhl M; Chaudhary, Kumardeep; Garmire, Lana X

2018-01-05

Metabolomics holds the promise as a new technology to diagnose highly heterogeneous diseases. Conventionally, metabolomics data analysis for diagnosis is done using various statistical and machine learning based classification methods. However, it remains unknown if deep neural network, a class of increasingly popular machine learning methods, is suitable to classify metabolomics data. Here we use a cohort of 271 breast cancer tissues, 204 positive estrogen receptor (ER+), and 67 negative estrogen receptor (ER-) to test the accuracies of feed-forward networks, a deep learning (DL) framework, as well as six widely used machine learning models, namely random forest (RF), support vector machines (SVM), recursive partitioning and regression trees (RPART), linear discriminant analysis (LDA), prediction analysis for microarrays (PAM), and generalized boosted models (GBM). DL framework has the highest area under the curve (AUC) of 0.93 in classifying ER+/ER- patients, compared to the other six machine learning algorithms. Furthermore, the biological interpretation of the first hidden layer reveals eight commonly enriched significant metabolomics pathways (adjusted P-value <0.05) that cannot be discovered by other machine learning methods. Among them, protein digestion and absorption and ATP-binding cassette (ABC) transporters pathways are also confirmed in integrated analysis between metabolomics and gene expression data in these samples. In summary, deep learning method shows advantages for metabolomics based breast cancer ER status classification, with both the highest prediction accuracy (AUC = 0.93) and better revelation of disease biology. We encourage the adoption of feed-forward networks based deep learning method in the metabolomics research community for classification.

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

PubMed

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.

Global metabolomic profiling targeting childhood obesity in the Hispanic population.

PubMed

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

2015-08-01

Metabolomics may unravel important biological pathways involved in the pathophysiology of childhood obesity. We aimed to 1) identify metabolites that differ significantly between nonobese and obese Hispanic children; 2) collapse metabolites into principal components (PCs) associated with obesity and metabolic risk, specifically hyperinsulinemia, hypertriglyceridemia, hyperleptinemia, and hyperuricemia; and 3) identify metabolites associated with energy expenditure and fat oxidation. This trial was a cross-sectional observational study of metabolomics by using gas chromatography-mass spectrometry and ultrahigh-performance liquid chromatography-tandem mass spectrometry analyses performed on fasting plasma samples from 353 nonobese and 450 obese Hispanic children. Branched-chained amino acids (BCAAs) (Leu, Ile, and Val) and their catabolites, propionylcarnitine and butyrylcarnitine, were significantly elevated in obese children. Strikingly lower lysolipids and dicarboxylated fatty acids were seen in obese children. Steroid derivatives were markedly higher in obese children as were markers of inflammation and oxidative stress. PC6 (BCAAs and aromatic AAs) and PC10 (asparagine, glycine, and serine) made the largest contributions to body mass index, and PC10 and PC12 (acylcarnitines) made the largest contributions to adiposity. Metabolic risk factors and total energy expenditure were associated with PC6, PC9 (AA and tricarboxylic acid cycle metabolites), and PC10. Fat oxidation was inversely related to PC8 (lysolipids) and positively related to PC16 (acylcarnitines). Global metabolomic profiling in nonobese and obese children replicates the increased BCAA and acylcarnitine catabolism and changes in nucleotides, lysolipids, and inflammation markers seen in obese adults; however, a strong signature of reduced fatty acid catabolism and increased steroid derivatives may be unique to obese children. Metabolic flexibility in fuel use observed in obese children may occur through the activation of alternative intermediary pathways. Insulin resistance, hyperleptinemia, hypertriglyceridemia, hyperuricemia, and oxidative stress and inflammation evident in obese children are associated with distinct metabolomic profiles. © 2015 American Society for Nutrition.

The Role of Plasma and Urine Metabolomics in Identifying New Biomarkers in Severe Newborn Asphyxia: A Study of Asphyxiated Newborn Pigs following Cardiopulmonary Resuscitation.

PubMed

Sachse, Daniel; Solevåg, Anne Lee; Berg, Jens Petter; Nakstad, Britt

2016-01-01

Optimizing resuscitation is important to prevent morbidity and mortality from perinatal asphyxia. The metabolism of cells and tissues is severely disturbed during asphyxia and resuscitation, and metabolomic analyses provide a snapshot of many small molecular weight metabolites in body fluids or tissues. In this study metabolomics profiles were studied in newborn pigs that were asphyxiated and resuscitated using different protocols to identify biomarkers for subject characterization, intervention effects and possibly prognosis. A total of 125 newborn Noroc pigs were anesthetized, mechanically ventilated and inflicted progressive asphyxia until asystole. Pigs were randomized to resuscitation with a FiO2 0.21 or 1.0, different duration of ventilation before initiation of chest compressions (CC), and different CC to ventilation ratios. Plasma and urine samples were obtained at baseline, and 2 h and 4 h after return of spontaneous circulation (ROSC, heart rate > = 100 bpm). Metabolomics profiles of the samples were analyzed by nuclear magnetic resonance spectroscopy. Plasma and urine showed severe metabolic alterations consistent with hypoxia and acidosis 2 h and 4 h after ROSC. Baseline plasma hypoxanthine and lipoprotein concentrations were inversely correlated to the duration of hypoxia sustained before asystole occurred, but there was no evidence for a differential metabolic response to the different resuscitation protocols or in terms of survival. Metabolic profiles of asphyxiated newborn pigs showed severe metabolic alterations. Consistent with previously published reports, we found no evidence of differences between established and alternative resuscitation protocols. Lactate and pyruvate may have a prognostic value, but have to be independently confirmed.

Metabolomic profiling in perinatal asphyxia: a promising new field.

PubMed

Denihan, Niamh M; Boylan, Geraldine B; Murray, Deirdre M

2015-01-01

Metabolomics, the latest "omic" technology, is defined as the comprehensive study of all low molecular weight biochemicals, "metabolites" present in an organism. As a systems biology approach, metabolomics has huge potential to progress our understanding of perinatal asphyxia and neonatal hypoxic-ischaemic encephalopathy, by uniquely detecting rapid biochemical pathway alterations in response to the hypoxic environment. The study of metabolomic biomarkers in the immediate neonatal period is not a trivial task and requires a number of specific considerations, unique to this disease and population. Recruiting a clearly defined cohort requires standardised multicentre recruitment with broad inclusion criteria and the participation of a range of multidisciplinary staff. Minimally invasive biospecimen collection is a priority for biomarker discovery. Umbilical cord blood presents an ideal medium as large volumes can be easily extracted and stored and the sample is not confounded by postnatal disease progression. Pristine biobanking and phenotyping are essential to ensure the validity of metabolomic findings. This paper provides an overview of the current state of the art in the field of metabolomics in perinatal asphyxia and neonatal hypoxic-ischaemic encephalopathy. We detail the considerations required to ensure high quality sampling and analysis, to support scientific progression in this important field.

Metabolomic Profiling in Perinatal Asphyxia: A Promising New Field

PubMed Central

Denihan, Niamh M.; Boylan, Geraldine B.; Murray, Deirdre M.

2015-01-01

Metabolomics, the latest “omic” technology, is defined as the comprehensive study of all low molecular weight biochemicals, “metabolites” present in an organism. As a systems biology approach, metabolomics has huge potential to progress our understanding of perinatal asphyxia and neonatal hypoxic-ischaemic encephalopathy, by uniquely detecting rapid biochemical pathway alterations in response to the hypoxic environment. The study of metabolomic biomarkers in the immediate neonatal period is not a trivial task and requires a number of specific considerations, unique to this disease and population. Recruiting a clearly defined cohort requires standardised multicentre recruitment with broad inclusion criteria and the participation of a range of multidisciplinary staff. Minimally invasive biospecimen collection is a priority for biomarker discovery. Umbilical cord blood presents an ideal medium as large volumes can be easily extracted and stored and the sample is not confounded by postnatal disease progression. Pristine biobanking and phenotyping are essential to ensure the validity of metabolomic findings. This paper provides an overview of the current state of the art in the field of metabolomics in perinatal asphyxia and neonatal hypoxic-ischaemic encephalopathy. We detail the considerations required to ensure high quality sampling and analysis, to support scientific progression in this important field. PMID:25802843

Applying Metabolomics to differentiate amphibian responses ...

EPA Pesticide Factsheets

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

Applied metabolomics in drug discovery.

PubMed

Cuperlovic-Culf, M; Culf, A S

2016-08-01

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

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

PubMed

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

2015-11-01

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

SECIMTools: a suite of metabolomics data analysis tools.

PubMed

Kirpich, Alexander S; Ibarra, Miguel; Moskalenko, Oleksandr; Fear, Justin M; Gerken, Joseph; Mi, Xinlei; Ashrafi, Ali; Morse, Alison M; McIntyre, Lauren M

2018-04-20

Metabolomics has the promise to transform the area of personalized medicine with the rapid development of high throughput technology for untargeted analysis of metabolites. Open access, easy to use, analytic tools that are broadly accessible to the biological community need to be developed. While technology used in metabolomics varies, most metabolomics studies have a set of features identified. Galaxy is an open access platform that enables scientists at all levels to interact with big data. Galaxy promotes reproducibility by saving histories and enabling the sharing workflows among scientists. SECIMTools (SouthEast Center for Integrated Metabolomics) is a set of Python applications that are available both as standalone tools and wrapped for use in Galaxy. The suite includes a comprehensive set of quality control metrics (retention time window evaluation and various peak evaluation tools), visualization techniques (hierarchical cluster heatmap, principal component analysis, modular modularity clustering), basic statistical analysis methods (partial least squares - discriminant analysis, analysis of variance, t-test, Kruskal-Wallis non-parametric test), advanced classification methods (random forest, support vector machines), and advanced variable selection tools (least absolute shrinkage and selection operator LASSO and Elastic Net). SECIMTools leverages the Galaxy platform and enables integrated workflows for metabolomics data analysis made from building blocks designed for easy use and interpretability. Standard data formats and a set of utilities allow arbitrary linkages between tools to encourage novel workflow designs. The Galaxy framework enables future data integration for metabolomics studies with other omics data.

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

PubMed

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

2017-09-01

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

Covering Chemical Diversity of Genetically-Modified Tomatoes Using Metabolomics for Objective Substantial Equivalence Assessment

PubMed Central

Hirai, Tadayoshi; Oikawa, Akira; Matsuda, Fumio; Fukushima, Atsushi; Arita, Masanori; Watanabe, Shin; Yano, Megumu; Hiwasa-Tanase, Kyoko; Ezura, Hiroshi; Saito, Kazuki

2011-01-01

As metabolomics can provide a biochemical snapshot of an organism's phenotype it is a promising approach for charting the unintended effects of genetic modification. A critical obstacle for this application is the inherently limited metabolomic coverage of any single analytical platform. We propose using multiple analytical platforms for the direct acquisition of an interpretable data set of estimable chemical diversity. As an example, we report an application of our multi-platform approach that assesses the substantial equivalence of tomatoes over-expressing the taste-modifying protein miraculin. In combination, the chosen platforms detected compounds that represent 86% of the estimated chemical diversity of the metabolites listed in the LycoCyc database. Following a proof-of-safety approach, we show that % had an acceptable range of variation while simultaneously indicating a reproducible transformation-related metabolic signature. We conclude that multi-platform metabolomics is an approach that is both sensitive and robust and that it constitutes a good starting point for characterizing genetically modified organisms. PMID:21359231

Stable isotope-resolved metabolomics and applications for drug development

PubMed Central

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

2012-01-01

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

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

PubMed

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

2017-10-01

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

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

PubMed

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

2009-09-01

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

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

PubMed Central

Serkova, Natalie J.; Standiford, Theodore J.

2011-01-01

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

Metabolomics: the apogee of the omic triology

PubMed Central

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

2013-01-01

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

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

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

Bingol, Kerem

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

Supporting metabolomics with adaptable software: design architectures for the end-user.

PubMed

Sarpe, Vladimir; Schriemer, David C

2017-02-01

Large and disparate sets of LC-MS data are generated by modern metabolomics profiling initiatives, and while useful software tools are available to annotate and quantify compounds, the field requires continued software development in order to sustain methodological innovation. Advances in software development practices allow for a new paradigm in tool development for metabolomics, where increasingly the end-user can develop or redeploy utilities ranging from simple algorithms to complex workflows. Resources that provide an organized framework for development are described and illustrated with LC-MS processing packages that have leveraged their design tools. Full access to these resources depends in part on coding experience, but the emergence of workflow builders and pluggable frameworks strongly reduces the skill level required. Developers in the metabolomics community are encouraged to use these resources and design content for uptake and reuse. Copyright © 2016 Elsevier Ltd. All rights reserved.

Delving deeper into technological innovations to understand differences in rice quality.

PubMed

Calingacion, Mariafe; Fang, Lu; Quiatchon-Baeza, Lenie; Mumm, Roland; Riedel, Arthur; Hall, Robert D; Fitzgerald, Melissa

2015-12-01

Increasing demand for better quality rice varieties, which are also more suited to growth under sub-optimal cultivation conditions, is driving innovation in rice research. Here we have used a multi-disciplinary approach, involving SNP-based genotyping together with phenotyping based on yield analysis, metabolomic analysis of grain volatiles, and sensory panel analysis to determine differences between two contrasting rice varieties, Apo and IR64. Plants were grown under standard and drought-induced conditions. Results revealed important differences between the volatile profiles of the two rice varieties and we relate these differences to those perceived by the sensory panel. Apo, which is the more drought tolerant variety, was less affected by the drought condition concerning both sensory profile and yield; IR64, which has higher quality but is drought sensitive, showed greater differences in these characteristics in response to the two growth conditions. Metabolomics analyses using GCxGC-MS, followed by multivariate statistical analyses of the data, revealed a number of discriminatory compounds between the varieties, but also effects of the difference in cultivation conditions. Results indicate the complexity of rice volatile profile, even of non-aromatic varieties, and how metabolomics can be used to help link changes in aroma profile with the sensory phenotype. Our outcomes also suggest valuable multi-disciplinary approaches which can be used to help define the aroma profile in rice, and its underlying genetic background, in order to support breeders in the generation of improved rice varieties combining high yield with high quality, and tolerance of both these traits to climate change.

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

NASA Astrophysics Data System (ADS)

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

2016-04-01

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

Metabolomic Profiles of Aspergillus oryzae and Bacillus amyloliquefaciens During Rice Koji Fermentation.

PubMed

Lee, Da Eun; Lee, Sunmin; Jang, Eun Seok; Shin, Hye Won; Moon, Byoung Seok; Lee, Choong Hwan

2016-06-14

Rice koji, used early in the manufacturing process for many fermented foods, produces diverse metabolites and enzymes during fermentation. Using gas chromatography time-of-flight mass spectrometry (GC-TOF-MS), ultrahigh-performance liquid chromatography linear trap quadrupole ion trap tandem mass spectrometry (UHPLC-LTQ-IT-MS/MS), and multivariate analysis we generated the metabolite profiles of rice koji produced by fermentation with Aspergillus oryzae (RK_AO) or Bacillus amyloliquefaciens (RK_BA) for different durations. Two principal components of the metabolomic data distinguished the rice koji samples according to their fermenter species and fermentation time. Several enzymes secreted by the fermenter species, including α-amylase, protease, and β-glucosidase, were assayed to identify differences in expression levels. This approach revealed that carbohydrate metabolism, serine-derived amino acids, and fatty acids were associated with rice koji fermentation by A. oryzae, whereas aromatic and branched chain amino acids, flavonoids, and lysophospholipids were more typical in rice koji fermentation by B. amyloliquefaciens. Antioxidant activity was significantly higher for RK_BA than for RK_AO, as were the abundances of flavonoids, including tricin, tricin glycosides, apigenin glycosides, and chrysoeriol glycosides. In summary, we have used MS-based metabolomics and enzyme activity assays to evaluate the effects of using different microbial species and fermentation times on the nutritional profile of rice koji.

Metabolomic profile of systemic sclerosis patients.

PubMed

Murgia, Federica; Svegliati, Silvia; Poddighe, Simone; Lussu, Milena; Manzin, Aldo; Spadoni, Tatiana; Fischetti, Colomba; Gabrielli, Armando; Atzori, Luigi

2018-05-16

Systemic sclerosis (SSc) is an autoimmune disease of unknown aetiology characterized by vascular lesions, immunological alterations and diffuse fibrosis of the skin and internal organs. Since recent evidence suggests that there is a link between metabolomics and immune mediated disease, serum metabolic profile of SSc patients and healthy controls was investigated by 1 H-NMR and GC-MS techniques. The results indicated a lower level of aspartate, alanine, choline, glutamate, and glutarate in SSc patients compared with healthy controls. Moreover, comparing patients affected by limited SSc (lcSSc) and diffuse SSc (dcSSc), 6 discriminant metabolites were identified. The multivariate analysis performed using all the metabolites significantly different revealed glycolysis, gluconeogenesis, energetic pathways, glutamate metabolism, degradation of ketone bodies and pyruvate metabolism as the most important networks. Aspartate, alanine and citrate yielded a high area under receiver-operating characteristic (ROC) curves (AUC of 0.81; CI 0.726-0.93) for discriminating SSc patients from controls, whereas ROC curve generated with acetate, fructose, glutamate, glutamine, glycerol and glutarate (AUC of 0.84; CI 0.7-0.98) discriminated between lcSSc and dcSSc. These results indicated that serum NMR-based metabolomics profiling method is sensitive and specific enough to distinguish SSc from healthy controls and provided a feasible diagnostic tool for the diagnosis and classification of the disease.

A Multi-Omic Systems-Based Approach Reveals Metabolic Markers of Bacterial Vaginosis and Insight into the Disease

PubMed Central

Yeoman, Carl J.; Thomas, Susan M.; Miller, Margret E. Berg; Ulanov, Alexander V.; Torralba, Manolito; Lucas, Sarah; Gillis, Marcus; Cregger, Melissa; Gomez, Andres; Ho, Mengfei; Leigh, Steven R.; Stumpf, Rebecca; Creedon, Douglas J.; Smith, Michael A.; Weisbaum, Jon S.; Nelson, Karen E.; Wilson, Brenda A.; White, Bryan A.

2013-01-01

Background Bacterial vaginosis (BV) is the most common vaginal disorder of reproductive-age women. Yet the cause of BV has not been established. To uncover key determinants of BV, we employed a multi-omic, systems-biology approach, including both deep 16S rRNA gene-based sequencing and metabolomics of lavage samples from 36 women. These women varied demographically, behaviorally, and in terms of health status and symptoms. Principal Findings 16S rRNA gene-based community composition profiles reflected Nugent scores, but not Amsel criteria. In contrast, metabolomic profiles were markedly more concordant with Amsel criteria. Metabolomic profiles revealed two distinct symptomatic BV types (SBVI and SBVII) with similar characteristics that indicated disruption of epithelial integrity, but each type was correlated to the presence of different microbial taxa and metabolites, as well as to different host behaviors. The characteristic odor associated with BV was linked to increases in putrescine and cadaverine, which were both linked to Dialister spp. Additional correlations were seen with the presence of discharge, 2-methyl-2-hydroxybutanoic acid, and Mobiluncus spp., and with pain, diethylene glycol and Gardnerella spp. Conclusions The results not only provide useful diagnostic biomarkers, but also may ultimately provide much needed insight into the determinants of BV. PMID:23405259

A multi-omic systems-based approach reveals metabolic markers of bacterial vaginosis and insight into the disease.

PubMed

Yeoman, Carl J; Thomas, Susan M; Miller, Margret E Berg; Ulanov, Alexander V; Torralba, Manolito; Lucas, Sarah; Gillis, Marcus; Cregger, Melissa; Gomez, Andres; Ho, Mengfei; Leigh, Steven R; Stumpf, Rebecca; Creedon, Douglas J; Smith, Michael A; Weisbaum, Jon S; Nelson, Karen E; Wilson, Brenda A; White, Bryan A

2013-01-01

Bacterial vaginosis (BV) is the most common vaginal disorder of reproductive-age women. Yet the cause of BV has not been established. To uncover key determinants of BV, we employed a multi-omic, systems-biology approach, including both deep 16S rRNA gene-based sequencing and metabolomics of lavage samples from 36 women. These women varied demographically, behaviorally, and in terms of health status and symptoms. 16S rRNA gene-based community composition profiles reflected Nugent scores, but not Amsel criteria. In contrast, metabolomic profiles were markedly more concordant with Amsel criteria. Metabolomic profiles revealed two distinct symptomatic BV types (SBVI and SBVII) with similar characteristics that indicated disruption of epithelial integrity, but each type was correlated to the presence of different microbial taxa and metabolites, as well as to different host behaviors. The characteristic odor associated with BV was linked to increases in putrescine and cadaverine, which were both linked to Dialister spp. Additional correlations were seen with the presence of discharge, 2-methyl-2-hydroxybutanoic acid, and Mobiluncus spp., and with pain, diethylene glycol and Gardnerella spp. The results not only provide useful diagnostic biomarkers, but also may ultimately provide much needed insight into the determinants of BV.

Metabolomic profiling reveals deep chemical divergence between two morphotypes of the zoanthid Parazoanthus axinellae

PubMed Central

Cachet, Nadja; Genta-Jouve, Grégory; Ivanisevic, Julijana; Chevaldonné, Pierre; Sinniger, Frédéric; Culioli, Gérald; Pérez, Thierry; Thomas, Olivier P.

2015-01-01

Metabolomics has recently proven its usefulness as complementary tool to traditional morphological and genetic analyses for the classification of marine invertebrates. Among the metabolite-rich cnidarian order Zoantharia, Parazoanthus is a polyphyletic genus whose systematics and phylogeny remain controversial. Within this genus, one of the most studied species, Parazoanthus axinellae is prominent in rocky shallow waters of the Mediterranean Sea and the NE Atlantic Ocean. Although different morphotypes can easily be distinguished, only one species is recognized to date. Here, a metabolomic profiling approach has been used to assess the chemical diversity of two main Mediterranean morphotypes, the “slender” and “stocky” forms of P. axinellae. Targeted profiling of their major secondary metabolites revealed a significant chemical divergence between the morphotypes. While zoanthoxanthin alkaloids and ecdysteroids are abundant in both morphs, the “slender” morphotype is characterized by the presence of additional and bioactive 3,5-disubstituted hydantoin derivatives named parazoanthines. The absence of these specific compounds in the “stocky” morphotype was confirmed by spatial and temporal monitoring over an annual cycle. Moreover, specimens of the “slender” morphotype are also the only ones found as epibionts of several sponge species, particularly Cymbaxinella damicornis thus suggesting a putative ecological link. PMID:25655432

Multi-omic profiles of hepatic metabolism in TPN-fed preterm pigs

USDA-ARS?s Scientific Manuscript database

New generation lipid emulsions comprised of fish oil or blends of soybean/fish/medium chain triglyceride/olive oil are emerging that result in favorable clinical metabolic outcomes in pediatric populations. Our aim was to characterize the lipidodomic, metabolomic, and transcriptomic profiles these ...

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

PubMed

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

2017-02-02

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

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

PubMed

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

2018-01-16

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

Salivary metabolomics in the diagnosis of oral cancer and periodontal diseases.

PubMed

Mikkonen, J J W; Singh, S P; Herrala, M; Lappalainen, R; Myllymaa, S; Kullaa, A M

2016-08-01

Metabolomics is a systemic study of metabolites, which are small molecules generated by the process of metabolism. The metabolic profile of saliva can provide an early outlook of the changes associated with a wide range of diseases, including oral cancer and periodontal diseases. It is possible to measure levels of disease-specific metabolites using different methods as presented in this study. However, many challenges exist including incomplete understanding of the complicated metabolic pathways of different oral diseases. The review concludes with the discussion on future perspectives of salivary metabolomics from a clinician point of view. Salivary metabolomics may afford a new research avenue to identify local and systemic disorders but also to aid in the design and modification of therapies. A MEDLINE search using keywords "salivary metabolomics" returned 23 results in total, of which seven were omitted for being reviews or letters to the editor. The rest of the articles were used for preparation of the review, 13 of these were published in the last 5 years. © 2015 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Decoding the dynamics of cellular metabolism and the action of 3-bromopyruvate and 2-deoxyglucose using pulsed stable isotope-resolved metabolomics.

PubMed

Pietzke, Matthias; Zasada, Christin; Mudrich, Susann; Kempa, Stefan

2014-01-01

Cellular metabolism is highly dynamic and continuously adjusts to the physiological program of the cell. The regulation of metabolism appears at all biological levels: (post-) transcriptional, (post-) translational, and allosteric. This regulatory information is expressed in the metabolome, but in a complex manner. To decode such complex information, new methods are needed in order to facilitate dynamic metabolic characterization at high resolution. Here, we describe pulsed stable isotope-resolved metabolomics (pSIRM) as a tool for the dynamic metabolic characterization of cellular metabolism. We have adapted gas chromatography-coupled mass spectrometric methods for metabolomic profiling and stable isotope-resolved metabolomics. In addition, we have improved robustness and reproducibility and implemented a strategy for the absolute quantification of metabolites. By way of examples, we have applied this methodology to characterize central carbon metabolism of a panel of cancer cell lines and to determine the mode of metabolic inhibition of glycolytic inhibitors in times ranging from minutes to hours. Using pSIRM, we observed that 2-deoxyglucose is a metabolic inhibitor, but does not directly act on the glycolytic cascade.

Metabolome strategy against Edwardsiella tarda infection through glucose-enhanced metabolic modulation in tilapias.

PubMed

Peng, Bo; Ma, Yan-Mei; Zhang, Jian-Ying; Li, Hui

2015-08-01

Edwardsiella tarda causes fish disease and great economic loss. However, metabolic strategy against the pathogen remains unexplored. In the present study, GC-MS based metabolomics was used to investigate the metabolic profile from tilapias infected by sublethal dose of E. tarda. The metabolic differences between the dying group and survival group allow the identification of key pathways and crucial metabolites during infections. More importantly, those metabolites may modulate the survival-related metabolome to enhance the anti-infective ability. Our data showed that tilapias generated two different strategies, survival-metabolome and death-metabolome, to encounter EIB202 infection, leading to differential outputs of the survival and dying. Glucose was the most crucial biomarker, which was upregulated and downregulated in the survival and dying groups, respectively. Exogenous glucose by injection or oral administration enhanced hosts' ability against EIB202 infection and increased the chances of survival. These findings highlight that host mounts the metabolic strategy to cope with bacterial infection, from which crucial biomarkers may be identified to enhance the metabolic strategy. Copyright © 2015 Elsevier Ltd. All rights reserved.

Discovery of human urinary biomarkers of aronia-citrus juice intake by HPLC-q-TOF-based metabolomic approach.

PubMed

Llorach, Rafael; Medina, Sonia; García-Viguera, Cristina; Zafrilla, Pilar; Abellán, José; Jauregui, Olga; Tomás-Barberán, Francisco A; Gil-Izquierdo, Angel; Andrés-Lacueva, Cristina

2014-06-01

Metabolomics has emerged in the field of food and nutrition sciences as a powerful tool for doing profiling approaches. In this context, HPLC-q-TOF-based metabolomics approach was applied to unveil changes in the urinary metabolome in human subjects (n = 51, 23 men and 28 women) after regular aronia-citrus juice (AC-juice) intake (250 mL/day) during 16 weeks compared to individuals given a placebo beverage. Samples were analyzed by HPLC-q-TOF followed by multivariate data analysis (orthogonal signal filtering-partial least square discriminant analysis) that discriminated relevant mass features related to AC-juice intake. The results showed that biomarkers of AC-juice intake including metabolites coming from metabolism of food components as proline betaine, ferulic acid, and two unknown mercapturate derivatives were identified. Discovery of new biomarkers of food intake will help in the building up of the food metabolome and facilitate future insights into the mechanisms of action of dietary components in population health. © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Growth of Malignant Non-CNS Tumors Alters Brain Metabolome

PubMed Central

Kovalchuk, Anna; Nersisyan, Lilit; Mandal, Rupasri; Wishart, David; Mancini, Maria; Sidransky, David; Kolb, Bryan; Kovalchuk, Olga

2018-01-01

Cancer survivors experience numerous treatment side effects that negatively affect their quality of life. Cognitive side effects are especially insidious, as they affect memory, cognition, and learning. Neurocognitive deficits occur prior to cancer treatment, arising even before cancer diagnosis, and we refer to them as “tumor brain.” Metabolomics is a new area of research that focuses on metabolome profiles and provides important mechanistic insights into various human diseases, including cancer, neurodegenerative diseases, and aging. Many neurological diseases and conditions affect metabolic processes in the brain. However, the tumor brain metabolome has never been analyzed. In our study we used direct flow injection/mass spectrometry (DI-MS) analysis to establish the effects of the growth of lung cancer, pancreatic cancer, and sarcoma on the brain metabolome of TumorGraft™ mice. We found that the growth of malignant non-CNS tumors impacted metabolic processes in the brain, affecting protein biosynthesis, and amino acid and sphingolipid metabolism. The observed metabolic changes were similar to those reported for neurodegenerative diseases and brain aging, and may have potential mechanistic value for future analysis of the tumor brain phenomenon. PMID:29515623

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

PubMed

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

Metabolomics is the comprehensive study of the metabolome, the repertoire of biochemicals (or small molecules) present in cells, tissues, and body fluids. The study of metabolism at the global or "-omics" level is a rapidly growing field that has the potential to have a profound impact upon medical practice. At the center of metabolomics, is the concept that a person's metabolic state provides a close representation of that individual's overall health status. This metabolic state reflects what has been encoded by the genome, and modified by diet, environmental factors, and the gut microbiome. The metabolic profile provides a quantifiable readout of biochemical state from normal physiology to diverse pathophysiologies in a manner that is often not obvious from gene expression analyses. Today, clinicians capture only a very small part of the information contained in the metabolome, as they routinely measure only a narrow set of blood chemistry analytes to assess health and disease states. Examples include measuring glucose to monitor diabetes, measuring cholesterol and high density lipoprotein/low density lipoprotein ratio to assess cardiovascular health, BUN and creatinine for renal disorders, and measuring a panel of metabolites to diagnose potential inborn errors of metabolism in neonates. We anticipate that the narrow range of chemical analyses in current use by the medical community today will be replaced in the future by analyses that reveal a far more comprehensive metabolic signature. This signature is expected to describe global biochemical aberrations that reflect patterns of variance in states of wellness, more accurately describe specific diseases and their progression, and greatly aid in differential diagnosis. Such future metabolic signatures will: (1) provide predictive, prognostic, diagnostic, and surrogate markers of diverse disease states; (2) inform on underlying molecular mechanisms of diseases; (3) allow for sub-classification of diseases, and stratification of patients based on metabolic pathways impacted; (4) reveal biomarkers for drug response phenotypes, providing an effective means to predict variation in a subject's response to treatment (pharmacometabolomics); (5) define a metabotype for each specific genotype, offering a functional read-out for genetic variants: (6) provide a means to monitor response and recurrence of diseases, such as cancers: (7) describe the molecular landscape in human performance applications and extreme environments. Importantly, sophisticated metabolomic analytical platforms and informatics tools have recently been developed that make it possible to measure thousands of metabolites in blood, other body fluids, and tissues. Such tools also enable more robust analysis of response to treatment. New insights have been gained about mechanisms of diseases, including neuropsychiatric disorders, cardiovascular disease, cancers, diabetes and a range of pathologies. A series of ground breaking studies supported by National Institute of Health (NIH) through the Pharmacometabolomics Research Network and its partnership with the Pharmacogenomics Research Network illustrate how a patient's metabotype at baseline, prior to treatment, during treatment, and post-treatment, can inform about treatment outcomes and variations in responsiveness to drugs (e.g., statins, antidepressants, antihypertensives and antiplatelet therapies). These studies along with several others also exemplify how metabolomics data can complement and inform genetic data in defining ethnic, sex, and gender basis for variation in responses to treatment, which illustrates how pharmacometabolomics and pharmacogenomics are complementary and powerful tools for precision medicine. Our metabolomics community believes that inclusion of metabolomics data in precision medicine initiatives is timely and will provide an extremely valuable layer of data that compliments and informs other data obtained by these important initiatives. Our Metabolomics Society, through its "Precision Medicine and Pharmacometabolomics Task Group", with input from our metabolomics community at large, has developed this White Paper where we discuss the value and approaches for including metabolomics data in large precision medicine initiatives. This White Paper offers recommendations for the selection of state of-the-art metabolomics platforms and approaches that offer the widest biochemical coverage, considers critical sample collection and preservation, as well as standardization of measurements, among other important topics. We anticipate that our metabolomics community will have representation in large precision medicine initiatives to provide input with regard to sample acquisition/preservation, selection of optimal omics technologies, and key issues regarding data collection, interpretation, and dissemination. We strongly recommend the collection and biobanking of samples for precision medicine initiatives that will take into consideration needs for large-scale metabolic phenotyping studies.

Investigation of the Antifatigue Effects of Korean Ginseng on Professional Athletes by Gas Chromatography-Time-of-Flight-Mass Spectrometry-Based Metabolomics.

PubMed

Yan, Bei; Liu, Yao; Shi, Aixin; Wang, Zhihong; Aa, Jiye; Huang, Xiaoping; Liu, Yi

2018-05-01

Ginseng is usually used for alleviating fatigue. The purpose of this paper was to evaluate the regulatory effect of Korean ginseng on the metabolic pattern in professional athletes, and, further, to explore the underlying mechanism of the antifatigue effect of Korean ginseng. GC-time-of-flight-MS was used to profile serum samples from professional athletes before training and after 15 and 30 day training, and professional athletes administered with Korean ginseng in the meanwhile. Biochemical parameters of all athletes were also analyzed. For the athlete control group, strength-endurance training resulted in an elevation of creatine kinase (CK) and blood urea nitrogen (BUN), and a reduction in blood hemoglobin, and a dynamic trajectory of the metabolomic profile which were related to fatigue. Korean ginseng treatment not only lead to a marked reduction in CK and blood urea nitrogen (BUN) in serum, but also showed regulatory effects on the serum metabolic profile and restored scores plots close to normal, suggesting that the change in metabolic profiling could reflect the antifatigue effect of Korean ginseng. Furthermore, perturbed levels of 11 endogenous metabolites were regulated by Korean ginseng significantly, which might be primarily involved in lipid metabolism, energy balance, and chemical signaling. These findings suggest that metabolomics is a potential tool for the evaluation of the antifatigue effect of Korean ginseng and for the elucidation of its pharmacological mechanism.

Evaluation of analytical performance and reliability of direct nanoLC-nanoESI-high resolution mass spectrometry for profiling the (xeno)metabolome.

PubMed

Chetwynd, Andrew J; David, Arthur; Hill, Elizabeth M; Abdul-Sada, Alaa

2014-10-01

Mass spectrometry (MS) profiling techniques are used for analysing metabolites and xenobiotics in biofluids; however, detection of low abundance compounds using conventional MS techniques is poor. To counter this, nanoflow ultra-high-pressure liquid chromatography-nanoelectrospray ionization-time-of-flight MS (nUHPLC-nESI-TOFMS), which has been used primarily for proteomics, offers an innovative prospect for profiling small molecules. Compared to conventional UHPLC-ESI-TOFMS, nUHPLC-nESI-TOFMS enhanced detection limits of a variety of (xeno)metabolites by between 2 and 2000-fold. In addition, this study demonstrates for the first time excellent repeatability and reproducibility for analysis of urine and plasma samples using nUHPLC-nESI-TOFMS, supporting implementation of this platform as a novel approach for high-throughput (xeno)metabolomics. Copyright © 2014 John Wiley & Sons, Ltd.

Metabolite profiling of antidepressant drug action reveals novel drug targets beyond monoamine elevation.

PubMed

Webhofer, C; Gormanns, P; Tolstikov, V; Zieglgänsberger, W; Sillaber, I; Holsboer, F; Turck, C W

2011-12-13

Currently used antidepressants elevate monoamine levels in the synaptic cleft. There is good reason to assume that this is not the only source for antidepressant therapeutic activities and that secondary downstream effects may be relevant for alleviating symptoms of depression. We attempted to elucidate affected biochemical pathways downstream of monoamine reuptake inhibition by interrogating metabolomic profiles in DBA/2Ola mice after chronic paroxetine treatment. Metabolomic changes were investigated using gas chromatography-mass spectrometry profiling and group differences were analyzed by univariate and multivariate statistics. Pathways affected by antidepressant treatment were related to energy metabolism, amino acid metabolism and hormone signaling. The identified pathways reveal further antidepressant therapeutic action and represent targets for drug development efforts. A comparison of the central nervous system with blood plasma metabolite alterations identified GABA, galactose-6-phosphate and leucine as biomarker candidates for assessment of antidepressant treatment effects in the periphery.

The Role of Plasma and Urine Metabolomics in Identifying New Biomarkers in Severe Newborn Asphyxia: A Study of Asphyxiated Newborn Pigs following Cardiopulmonary Resuscitation

PubMed Central

Sachse, Daniel; Solevåg, Anne Lee; Berg, Jens Petter; Nakstad, Britt

2016-01-01

Background Optimizing resuscitation is important to prevent morbidity and mortality from perinatal asphyxia. The metabolism of cells and tissues is severely disturbed during asphyxia and resuscitation, and metabolomic analyses provide a snapshot of many small molecular weight metabolites in body fluids or tissues. In this study metabolomics profiles were studied in newborn pigs that were asphyxiated and resuscitated using different protocols to identify biomarkers for subject characterization, intervention effects and possibly prognosis. Methods A total of 125 newborn Noroc pigs were anesthetized, mechanically ventilated and inflicted progressive asphyxia until asystole. Pigs were randomized to resuscitation with a FiO2 0.21 or 1.0, different duration of ventilation before initiation of chest compressions (CC), and different CC to ventilation ratios. Plasma and urine samples were obtained at baseline, and 2 h and 4 h after return of spontaneous circulation (ROSC, heart rate > = 100 bpm). Metabolomics profiles of the samples were analyzed by nuclear magnetic resonance spectroscopy. Results Plasma and urine showed severe metabolic alterations consistent with hypoxia and acidosis 2 h and 4 h after ROSC. Baseline plasma hypoxanthine and lipoprotein concentrations were inversely correlated to the duration of hypoxia sustained before asystole occurred, but there was no evidence for a differential metabolic response to the different resuscitation protocols or in terms of survival. Conclusions Metabolic profiles of asphyxiated newborn pigs showed severe metabolic alterations. Consistent with previously published reports, we found no evidence of differences between established and alternative resuscitation protocols. Lactate and pyruvate may have a prognostic value, but have to be independently confirmed. PMID:27529347

Heat-stabilised rice bran consumption by colorectal cancer survivors modulates stool metabolite profiles and metabolic networks: a randomised controlled trial

PubMed Central

Brown, Dustin G.; Borresen, Erica C.; Brown, Regina J.; Ryan, Elizabeth P.

2017-01-01

Rice bran (RB) consumption has been shown to reduce colorectal cancer (CRC) growth in mice and modify the human stool microbiome. Changes in host and microbial metabolism induced by RB consumption was hypothesised to modulate the stool metabolite profile in favour of promoting gut health and inhibiting CRC growth. The objective was to integrate gut microbial metabolite profiles and identify metabolic pathway networks for CRC chemoprevention using non-targeted metabolomics. In all, nineteen CRC survivors participated in a parallel randomised controlled dietary intervention trial that included daily consumption of study-provided foods with heat-stabilised RB (30 g/d) or no additional ingredient (control). Stool samples were collected at baseline and 4 weeks and analysed using GC-MS and ultra-performance liquid chromatography-MS. Stool metabolomics revealed 93 significantly different metabolites in individuals consuming RB. A 264-fold increase in β-hydroxyisovaleroylcarnitine and 18-fold increase in β-hydroxyisovalerate exemplified changes in leucine, isoleucine and valine metabolism in the RB group. A total of thirty-nine stool metabolites were significantly different between RB and control groups, including increased hesperidin (28-fold) and narirutin (14-fold). Metabolic pathways impacted in the RB group over time included advanced glycation end products, steroids and bile acids. Fatty acid, leucine/valine and vitamin B6 metabolic pathways were increased in RB compared with control. There were 453 metabolites identified in the RB food metabolome, thirty-nine of which were identified in stool from RB consumers. RB consumption favourably modulated the stool metabolome of CRC survivors and these findings suggest the need for continued dietary CRC chemoprevention efforts. PMID:28643618

Potential metabolomic biomarkers for reliable diagnosis of Behcet's disease using gas chromatography/ time-of-flight-mass spectrometry.

PubMed

Ahn, Joong Kyong; Kim, Jungyeon; Hwang, Jiwon; Song, Juhwan; Kim, Kyoung Heon; Cha, Hoon-Suk

2018-05-01

Although many diagnostic criteria of Behcet's disease (BD) have been developed and revised by experts, diagnosing BD is still complicated and challenging. No metabolomic studies on serum have been attempted to improve the diagnosis and to identify potential biomarkers of BD. The purposes of this study were to investigate distinctive metabolic changes in serum samples of BD patients and to identify metabolic candidate biomarkers for reliable diagnosis of BD using the metabolomics platform. Metabolomic profiling of 90 serum samples from 45 BD patients and 45 healthy controls (HCs) were performed via gas chromatography with time-of-flight mass spectrometry (GC/TOF-MS) with multivariate statistical analyses. A total of 104 metabolites were identified from samples. The serum metabolite profiles obtained from GC/TOF-MS analysis can distinguish BD patients from HC group in discovery set. The variation values of the partial least squared-discrimination analysis (PLS-DA) model are R 2 X of 0.246, R 2 Y of 0.913 and Q 2 of 0.852, respectively, indicating strong explanation and prediction capabilities of the model. A panel of five metabolic biomarkers, namely, decanoic acid, fructose, tagatose, linoleic acid and oleic acid were selected and adequately validated as putative biomarkers of BD (sensitivity 100%, specificity 97.1%, area under the curve 0.998) in the discovery set and independent set. The PLS_DA model showed clear discrimination of BD and HC groups by the five metabolic biomarkers in independent set. This is the first report on characteristic metabolic profiles and potential metabolite biomarkers in serum for reliable diagnosis of BD using GC/TOF-MS. Copyright © 2017. Published by Elsevier SAS.

A baseline metabolomic signature is associated with immunological CD4+ T-cell recovery after 36 months of antiretroviral therapy in HIV-infected patients.

PubMed

Rodríguez-Gallego, Esther; Gómez, Josep; Pacheco, Yolanda M; Peraire, Joaquim; Viladés, Consuelo; Beltrán-Debón, Raúl; Mallol, Roger; López-Dupla, Miguel; Veloso, Sergi; Alba, Verónica; Blanco, Julià; Cañellas, Nicolau; Rull, Anna; Leal, Manuel; Correig, Xavier; Domingo, Pere; Vidal, Francesc

2018-03-13

Poor immunological recovery in treated HIV-infected patients is associated with greater morbidity and mortality. To date, predictive biomarkers of this incomplete immune reconstitution have not been established. We aimed to identify a baseline metabolomic signature associated with a poor immunological recovery after antiretroviral therapy (ART) to envisage the underlying mechanistic pathways that influence the treatment response. This was a multicentre, prospective cohort study in ART-naive and a pre-ART low nadir (<200 cells/μl) HIV-infected patients (n = 64). We obtained clinical data and metabolomic profiles for each individual, in which low molecular weight metabolites, lipids and lipoproteins (including particle concentrations and sizes) were measured by NMR spectroscopy. Immunological recovery was defined as reaching CD4 T-cell count at least 250 cells/μl after 36 months of virologically successful ART. We used univariate comparisons, Random Forest test and receiver-operating characteristic curves to identify and evaluate the predictive factors of immunological recovery after treatment. HIV-infected patients with a baseline metabolic pattern characterized by high levels of large high density lipoprotein (HDL) particles, HDL cholesterol and larger sizes of low density lipoprotein particles had a better immunological recovery after treatment. Conversely, patients with high ratios of non-HDL lipoprotein particles did not experience this full recovery. Medium very-low-density lipoprotein particles and glucose increased the classification power of the multivariate model despite not showing any significant differences between the two groups. In HIV-infected patients, a baseline healthier metabolomic profile is related to a better response to ART where the lipoprotein profile, mainly large HDL particles, may play a key role.

Heat-stabilised rice bran consumption by colorectal cancer survivors modulates stool metabolite profiles and metabolic networks: a randomised controlled trial.

PubMed

Brown, Dustin G; Borresen, Erica C; Brown, Regina J; Ryan, Elizabeth P

2017-05-01

Rice bran (RB) consumption has been shown to reduce colorectal cancer (CRC) growth in mice and modify the human stool microbiome. Changes in host and microbial metabolism induced by RB consumption was hypothesised to modulate the stool metabolite profile in favour of promoting gut health and inhibiting CRC growth. The objective was to integrate gut microbial metabolite profiles and identify metabolic pathway networks for CRC chemoprevention using non-targeted metabolomics. In all, nineteen CRC survivors participated in a parallel randomised controlled dietary intervention trial that included daily consumption of study-provided foods with heat-stabilised RB (30 g/d) or no additional ingredient (control). Stool samples were collected at baseline and 4 weeks and analysed using GC-MS and ultra-performance liquid chromatography-MS. Stool metabolomics revealed 93 significantly different metabolites in individuals consuming RB. A 264-fold increase in β-hydroxyisovaleroylcarnitine and 18-fold increase in β-hydroxyisovalerate exemplified changes in leucine, isoleucine and valine metabolism in the RB group. A total of thirty-nine stool metabolites were significantly different between RB and control groups, including increased hesperidin (28-fold) and narirutin (14-fold). Metabolic pathways impacted in the RB group over time included advanced glycation end products, steroids and bile acids. Fatty acid, leucine/valine and vitamin B6 metabolic pathways were increased in RB compared with control. There were 453 metabolites identified in the RB food metabolome, thirty-nine of which were identified in stool from RB consumers. RB consumption favourably modulated the stool metabolome of CRC survivors and these findings suggest the need for continued dietary CRC chemoprevention efforts.

FODMAPs alter symptoms and the metabolome of patients with IBS: a randomised controlled trial.

PubMed

McIntosh, Keith; Reed, David E; Schneider, Theresa; Dang, Frances; Keshteli, Ammar H; De Palma, Giada; Madsen, Karen; Bercik, Premysl; Vanner, Stephen

2017-07-01

To gain mechanistic insights, we compared effects of low fermentable oligosaccharides, disaccharides and monosaccharides and polyols (FODMAP) and high FODMAP diets on symptoms, the metabolome and the microbiome of patients with IBS. We performed a controlled, single blind study of patients with IBS (Rome III criteria) randomised to a low (n=20) or high (n=20) FODMAP diet for 3 weeks. Symptoms were assessed using the IBS symptom severity scoring (IBS-SSS). The metabolome was evaluated using the lactulose breath test (LBT) and metabolic profiling in urine using mass spectrometry. Stool microbiota composition was analysed by 16S rRNA gene profiling. Thirty-seven patients (19 low FODMAP; 18 high FODMAP) completed the 3-week diet. The IBS-SSS was reduced in the low FODMAP diet group (p<0.001) but not the high FODMAP group. LBTs showed a minor decrease in H 2 production in the low FODMAP compared with the high FODMAP group. Metabolic profiling of urine showed groups of patients with IBS differed significantly after the diet (p<0.01), with three metabolites (histamine, p-hydroxybenzoic acid, azelaic acid) being primarily responsible for discrimination between the two groups. Histamine, a measure of immune activation, was reduced eightfold in the low FODMAP group (p<0.05). Low FODMAP diet increased Actinobacteria richness and diversity, and high FODMAP diet decreased the relative abundance of bacteria involved in gas consumption. IBS symptoms are linked to FODMAP content and associated with alterations in the metabolome. In subsets of patients, FODMAPs modulate histamine levels and the microbiota, both of which could alter symptoms. NCT01829932. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/.

Heritable IUGR and adult metabolic syndrome are reversible and associated with alterations in the metabolome following dietary supplementation of 1-carbon intermediates

PubMed Central

Seferovic, Maxim D.; Goodspeed, Danielle M.; Chu, Derrick M.; Krannich, Laura A.; Gonzalez-Rodriguez, Pablo J.; Cox, James E.; Aagaard, Kjersti M.

2015-01-01

Metabolic syndrome (MetS), following intrauterine growth restriction (IUGR), is epigenetically heritable. Recently, we abrogated the F2 adult phenotype with essential nutrient supplementation (ENS) of intermediates along the 1-carbon pathway. With the use of the same grandparental uterine artery ligation model, we profiled the F2 serum metabolome at weaning [postnatal day (d)21; n = 76] and adulthood (d160; n = 12) to test if MetS is preceded by alterations in the metabolome. Indicative of developmentally programmed MetS, adult F2, formerly IUGR rats, were obese (621 vs. 461 g; P < 0.0001), dyslipidemic (133 vs. 67 mg/dl; P < 0.001), and glucose intolerant (26 vs. 15 mg/kg/min; P < 0.01). Unbiased gas chromatography-mass spectrometry (GC-MS) profiling revealed 34 peaks corresponding to 12 nonredundant metabolites and 9 unknowns to be changing at weaning [false discovery rate (FDR) < 0.05]. Markers of later-in-life MetS included citric acid, glucosamine, myoinositol, and proline (P < 0.03). Hierarchical clustering revealed grouping by IUGR lineage and supplementation at d21 and d160. Weanlings grouped distinctly for ENS and IUGR by partial least-squares discriminate analysis (PLS-DA; P < 0.01), whereas paternal and maternal IUGR (IUGRpat/IUGRmat, respectively) control-fed rats, destined for MetS, had a distinct metabolome at weaning (randomForest analysis; class error < 0.1) and adulthood (PLS-DA; P < 0.05). In sum, we have found that alterations in the metabolome accompany heritable IUGR, precede adult-onset MetS, and are partially amenable to dietary intervention.—Seferovic, M. D., Goodspeed, D. M., Chu, D. M., Krannich, L. A., Gonzalez-Rodriguez, P. J., Cox, J. E., Aagaard, K. M. Heritable IUGR and adult metabolic syndrome are reversible and associated with alterations in the metabolome following dietary supplementation of one-carbon intermediates. PMID:25757570

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

PubMed Central

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

2012-01-01

Background Hypoxic ischaemic encephalopathy (HIE) in newborns can cause significant long-term neurological disability. The insult is a complex injury characterised by energy failure and disruption of cellular homeostasis, leading to mitochondrial damage. The importance of individual metabolic pathways, and their interaction in the disease process is not fully understood. The aim of this study was to describe and quantify the metabolomic profile of umbilical cord blood samples in a carefully defined population of full-term infants with HIE. Methods and Findings The injury severity was defined using both the modified Sarnat score and continuous multichannel electroencephalogram. Using these classification systems, our population was divided into those with confirmed HIE (n = 31), asphyxiated infants without encephalopathy (n = 40) and matched controls (n = 71). All had umbilical cord blood drawn and biobanked at −80°C within 3 hours of delivery. A combined direct injection and LC-MS/MS assay (AbsolutIDQ p180 kit, Biocrates Life Sciences AG, Innsbruck, Austria) was used for the metabolomic analyses of the samples. Targeted metabolomic analysis showed a significant alteration between study groups in 29 metabolites from 3 distinct classes (Amino Acids, Acylcarnitines, and Glycerophospholipids). 9 of these metabolites were only significantly altered between neonates with Hypoxic ischaemic encephalopathy and matched controls, while 14 were significantly altered in both study groups. Multivariate Discriminant Analysis models developed showed clear multifactorial metabolite associations with both asphyxia and HIE. A logistic regression model using 5 metabolites clearly delineates severity of asphyxia and classifies HIE infants with AUC = 0.92. These data describe wide-spread disruption to not only energy pathways, but also nitrogen and lipid metabolism in both asphyxia and HIE. Conclusion This study shows that a multi-platform targeted approach to metabolomic analyses using accurately phenotyped and meticulously biobanked samples provides insight into the pathogenesis of perinatal asphyxia. It highlights the potential for metabolomic technology to develop a diagnostic test for HIE. PMID:23227182

A Metabolic Profiling Strategy for the Dissection of Plant Defense against Fungal Pathogens

PubMed Central

Aliferis, Konstantinos A.; Faubert, Denis; Jabaji, Suha

2014-01-01

Here we present a metabolic profiling strategy employing direct infusion Orbitrap mass spectrometry (MS) and gas chromatography-mass spectrometry (GC/MS) for the monitoring of soybean's (Glycine max L.) global metabolism regulation in response to Rhizoctonia solani infection in a time-course. Key elements in the approach are the construction of a comprehensive metabolite library for soybean, which accelerates the steps of metabolite identification and biological interpretation of results, and bioinformatics tools for the visualization and analysis of its metabolome. The study of metabolic networks revealed that infection results in the mobilization of carbohydrates, disturbance of the amino acid pool, and activation of isoflavonoid, α-linolenate, and phenylpropanoid biosynthetic pathways of the plant. Components of these pathways include phytoalexins, coumarins, flavonoids, signaling molecules, and hormones, many of which exhibit antioxidant properties and bioactivity helping the plant to counterattack the pathogen's invasion. Unraveling the biochemical mechanism operating during soybean-Rhizoctonia interaction, in addition to its significance towards the understanding of the plant's metabolism regulation under biotic stress, provides valuable insights with potential for applications in biotechnology, crop breeding, and agrochemical and food industries. PMID:25369450

Phytochemical characterization of different prickly pear (Opuntia ficus-indica (L.) Mill.) cultivars and botanical parts: UHPLC-ESI-MSn metabolomics profiles and their chemometric analysis.

PubMed

Mena, Pedro; Tassotti, Michele; Andreu, Lucía; Nuncio-Jáuregui, Nallely; Legua, Pilar; Del Rio, Daniele; Hernández, Francisca

2018-06-01

Prickly pear is an important source of bioactive compounds. However, a comprehensive characterization of the phytochemical profile of its aerial botanical parts, considering genotypic differences, has not been conducted. This study evaluated the phytochemical composition of four botanical parts (fruit pulp and skin, and young and adult cladodes) of six cultivars. Analysis was carried out by using two non-targeted UHPLC-ESI-MS n experimental conditions and assisted with multivariate analysis to facilitate data interpretation. Up to 41 compounds, mainly (poly)phenolic molecules, were identified and quantified, 23 compounds being reported for the first time in Opuntia ficus-indica. Phenolic composition varied significantly depending on the part of the plant. Betalains were detected only in the fruit of a red cultivar. This study provided novel insights in terms of identification of bioactives and thorough characterization of botanical parts of prickly pears. This information may be used for the development of prickly pear-derived products with high levels of bioactive compounds. Copyright © 2018 Elsevier Ltd. All rights reserved.

Blood Transcriptomics and Metabolomics for Personalized Medicine

DTIC Science & Technology

2015-10-31

the network by taking addi- tional information as priors. For example, genes with cis-eQTLs (cis means locally acting on a genomic sequence ) could be...Lander ES. Initial impact of the sequencing of the human genome . Nature 2011; 470(7333):187–97. [9] Manolio TA, et al. Finding the missing heritability of...2010;6(2). [80] Hoffman JM, et al. Effects of age, sex, and genotype on high-sensitivity metabolomic profiles in the fruit fly, Drosophila melanogaster

Human Metabolome Associates With Dietary Intake Habits Among African Americans in the Atherosclerosis Risk in Communities Study

PubMed Central

Zheng, Yan; Yu, Bing; Alexander, Danny; Steffen, Lyn M.; Boerwinkle, Eric

2014-01-01

The human metabolome is a measurable outcome of interactions among an individual's inherited genome, microbiome, and dietary intake. We explored the relationship between dietary intake and serum untargeted metabolomic profiles in a subsample of 1,977 African Americans from the Atherosclerosis Risk in Communities (ARIC) Study in 1987–1989. For each metabolite, we conducted linear regression to estimate its relationships with each food group and food category. Potential confounding factors included age, sex, body mass index (weight (kg)/height (m)2), energy intake, kidney function, and food groups. We used a modified Bonferroni correction to determine statistical significance. In total, 48 pairs of diet-metabolite associations were identified, including multiple novel associations. The food group “sugar-rich foods and beverages” was inversely associated with 5 metabolites in the 2-hydroxybutyrate–related subpathway and positively associated with 5 γ-glutamyl dipeptides. The hypothesized mechanism of these associations may be through oxidative stress. “Sugar-rich foods and beverages” were also inversely associated with 7 unsaturated long-chain fatty acids. These findings suggest that the contribution of a sugar-rich dietary pattern to increased cardiovascular disease risk may be partially attributed to oxidative stress and disordered lipid profiles. Metabolomics may reveal novel metabolic biomarkers of dietary intake and provide insight into biochemical pathways underlying nutritional effects on disease development. PMID:24801555

Metabolomic biomarkers correlating with hepatic lipidosis in dairy cows.

PubMed

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

2014-06-02

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

Impact in Plasma Metabolome as Effect of Lifestyle Intervention for Weight-Loss Reveals Metabolic Benefits in Metabolically Healthy Obese Women.

PubMed

Almanza-Aguilera, Enrique; Brunius, Carl; Bernal-Lopez, M Rosa; Garcia-Aloy, Mar; Madrid-Gambin, Francisco; Tinahones, Francisco J; Gómez-Huelgas, Ricardo; Landberg, Rikard; Andres-Lacueva, Cristina

2018-06-28

Little is known regarding metabolic benefits of weight loss (WL) on the metabolically healthy obese (MHO) patients. We aimed to examine the impact of a lifestyle weight loss (LWL) treatment on the plasma metabolomic profile in MHO individuals. Plasma samples from 57 MHO women allocated to an intensive LWL treatment group (TG, hypocaloric Mediterranean diet and regular physical activity, n = 30) or to a control group (CG, general recommendations of a healthy diet and physical activity, n = 27) were analyzed using an untargeted 1 H NMR metabolomics approach at baseline, after 3 months (intervention), and 12 months (follow-up). The impact of the LWL intervention on plasma metabolome was statistically significant at 3 months but not at follow-up and included higher levels of formate and phosphocreatine and lower levels of LDL/VLDL (signals) and trimethylamine in the TG. These metabolites were also correlated with WL. Higher myo-inositol, methylguanidine, and 3-hydroxybutyrate, and lower proline, were also found in the TG; higher levels of hippurate and asparagine, and lower levels of 2-hydroxybutyrate and creatine, were associated with WL. The current findings suggest that an intensive LWL treatment, and the consequent WL, leads to an improved plasma metabolic profile in MHO women through its impact on energy, amino acid, lipoprotein, and microbial metabolism.

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

PubMed

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

2016-09-09

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

Metabolomics evaluation of the impact of smokeless tobacco exposure on the oral bacterium Capnocytophaga sputigena

PubMed Central

Sun, Jinchun; Jin, Jinshan; Beger, Richard D.; Cerniglia, Carl E.; Yang, Maocheng; Chen, Huizhong

2017-01-01

The association between exposure to smokeless tobacco products (STP) and oral diseases is partially due to the physiological and pathological changes in the composition of the oral microbiome and its metabolic profile. However, it is not clear how STPs affect the physiology and ecology of oral microbiota. A UPLC/QTof-MS-based metabolomics study was employed to analyze metabolic alterations in oral bacterium, Capnocytophaga sputigena as a result of smokeless tobacco exposure and to assess the capability of the bacterium to metabolize nicotine. Pathway analysis of the metabolome profiles indicated that smokeless tobacco extracts caused oxidative stress in the bacterium. The metabolomics data also showed that the argininenitric oxide pathway was perturbed by the smokeless tobacco treatment. Results also showed that LC/MS was useful in identifying STP constituents and additives, including caffeine and many flavoring compounds. No significant changes in levels of nicotine and its major metabolites were found when C. sputigena was cultured in a nutrient rich medium, although hydroxylnicotine and cotinine N-oxide were detected in the bacterial metabolites suggesting that nicotine metabolism might be present as a minor degradation pathway in the bacterium. Study results provide new insights regarding the physiological and toxicological effects of smokeless tobacco on oral bacterium C. sputigena and associated oral health as well as measuring the ability of the oral bacterium to metabolize nicotine. PMID:27480511

Untargeted metabolomics unravels functionalities of phosphorylation sites in Saccharomyces cerevisiae.

PubMed

Raguz Nakic, Zrinka; Seisenbacher, Gerhard; Posas, Francesc; Sauer, Uwe

2016-11-15

Coordinated through a complex network of kinases and phosphatases, protein phosphorylation regulates essentially all cellular processes in eukaryotes. Recent advances in proteomics enable detection of thousands of phosphorylation sites (phosphosites) in single experiments. However, functionality of the vast majority of these sites remains unclear and we lack suitable approaches to evaluate functional relevance at a pace that matches their detection. Here, we assess functionality of 26 phosphosites by introducing phosphodeletion and phosphomimic mutations in 25 metabolic enzymes and regulators from the TOR and HOG signaling pathway in Saccharomyces cerevisiae by phenotypic analysis and untargeted metabolomics. We show that metabolomics largely outperforms growth analysis and recovers 10 out of the 13 previously characterized phosphosites and suggests functionality for several novel sites, including S79 on the TOR regulatory protein Tip41. We analyze metabolic profiles to identify consequences underlying regulatory phosphorylation events and detecting glycerol metabolism to have a so far unknown influence on arginine metabolism via phosphoregulation of the glycerol dehydrogenases. Further, we also find S508 in the MAPKK Pbs2 as a potential link for cross-talking between HOG signaling and the cell wall integrity pathway. We demonstrate that metabolic profiles can be exploited for gaining insight into regulatory consequences and biological roles of phosphosites. Altogether, untargeted metabolomics is a fast, sensitive and informative approach appropriate for future large-scale functional analyses of phosphosites.

Metabolomic biomarkers correlating with hepatic lipidosis in dairy cows

PubMed Central

2014-01-01

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

Metabolomics evaluation of the impact of smokeless tobacco exposure on the oral bacterium Capnocytophaga sputigena.

PubMed

Sun, Jinchun; Jin, Jinshan; Beger, Richard D; Cerniglia, Carl E; Yang, Maocheng; Chen, Huizhong

2016-10-01

The association between exposure to smokeless tobacco products (STP) and oral diseases is partially due to the physiological and pathological changes in the composition of the oral microbiome and its metabolic profile. However, it is not clear how STPs affect the physiology and ecology of oral microbiota. A UPLC/QTof-MS-based metabolomics study was employed to analyze metabolic alterations in oral bacterium, Capnocytophaga sputigena as a result of smokeless tobacco exposure and to assess the capability of the bacterium to metabolize nicotine. Pathway analysis of the metabolome profiles indicated that smokeless tobacco extracts caused oxidative stress in the bacterium. The metabolomics data also showed that the arginine-nitric oxide pathway was perturbed by the smokeless tobacco treatment. Results also showed that LC/MS was useful in identifying STP constituents and additives, including caffeine and many flavoring compounds. No significant changes in levels of nicotine and its major metabolites were found when C. sputigena was cultured in a nutrient rich medium, although hydroxylnicotine and cotinine N-oxide were detected in the bacterial metabolites suggesting that nicotine metabolism might be present as a minor degradation pathway in the bacterium. Study results provide new insights regarding the physiological and toxicological effects of smokeless tobacco on oral bacterium C. sputigena and associated oral health as well as measuring the ability of the oral bacterium to metabolize nicotine. Published by Elsevier Ltd.

Consensus-phenotype integration of transcriptomic and metabolomic data implies a role for metabolism in the chemosensitivity of tumour cells.

PubMed

Cavill, Rachel; Kamburov, Atanas; Ellis, James K; Athersuch, Toby J; Blagrove, Marcus S C; Herwig, Ralf; Ebbels, Timothy M D; Keun, Hector C

2011-03-01

Using transcriptomic and metabolomic measurements from the NCI60 cell line panel, together with a novel approach to integration of molecular profile data, we show that the biochemical pathways associated with tumour cell chemosensitivity to platinum-based drugs are highly coincident, i.e. they describe a consensus phenotype. Direct integration of metabolome and transcriptome data at the point of pathway analysis improved the detection of consensus pathways by 76%, and revealed associations between platinum sensitivity and several metabolic pathways that were not visible from transcriptome analysis alone. These pathways included the TCA cycle and pyruvate metabolism, lipoprotein uptake and nucleotide synthesis by both salvage and de novo pathways. Extending the approach across a wide panel of chemotherapeutics, we confirmed the specificity of the metabolic pathway associations to platinum sensitivity. We conclude that metabolic phenotyping could play a role in predicting response to platinum chemotherapy and that consensus-phenotype integration of molecular profiling data is a powerful and versatile tool for both biomarker discovery and for exploring the complex relationships between biological pathways and drug response.

Serum Metabolomic Profiling of Piglets Infected with Virulent Classical Swine Fever Virus

PubMed Central

Gong, Wenjie; Jia, Junjie; Zhang, Bikai; Mi, Shijiang; Zhang, Li; Xie, Xiaoming; Guo, Huancheng; Shi, Jishu; Tu, Changchun

2017-01-01

Classical swine fever (CSF) is a highly contagious swine infectious disease and causes significant economic losses for the pig industry worldwide. The objective of this study was to determine whether small molecule metabolites contribute to the pathogenesis of CSF. Birefly, serum metabolomics of CSFV Shimen strain-infected piglets were analyzed by ultraperformance liquid chromatography/electrospray ionization time-of-flight mass spectrometry (UPLC/ESI-Q-TOF/MS) in combination with multivariate statistical analysis. In CSFV-infected piglets at days 3 and 7 post-infection changes were found in metabolites associated with several key metabolic pathways, including tryptophan catabolism and the kynurenine pathway, phenylalanine metabolism, fatty acid and lipid metabolism, the tricarboxylic acid and urea cycles, branched-chain amino acid metabolism, and nucleotide metabolism. Several pathways involved in energy metabolism including fatty acid biosynthesis and β-oxidation, branched-chain amino acid metabolism, and the tricarboxylic acid cycle were significantly inhibited. Changes were also observed in several metabolites exclusively associated with gut microbiota. The metabolomic profiles indicate that CSFV-host gut microbiome interactions play a role in the development of CSF. PMID:28496435

Urinary metabolomic profiling in mice with diet-induced obesity and type 2 diabetes mellitus after treatment with metformin, vildagliptin and their combination.

PubMed

Pelantová, Helena; Bugáňová, Martina; Holubová, Martina; Šedivá, Blanka; Zemenová, Jana; Sýkora, David; Kaválková, Petra; Haluzík, Martin; Železná, Blanka; Maletínská, Lenka; Kuneš, Jaroslav; Kuzma, Marek

2016-08-15

Metformin, vildagliptin and their combination are widely used for the treatment of diabetes, but little is known about the metabolic responses to these treatments. In the present study, NMR-based metabolomics was applied to detect changes in the urinary metabolomic profile of a mouse model of diet-induced obesity in response to these treatments. Additionally, standard biochemical parameters and the expression of enzymes involved in glucose and fat metabolism were monitored. Significant correlations were observed between several metabolites (e.g., N-carbamoyl-β-alanine, N1-methyl-4-pyridone-3-carboxamide, N1-methyl-2-pyridone-5-carboxamide, glucose, 3-indoxyl sulfate, dimethylglycine and several acylglycines) and the area under the curve of glucose concentrations during the oral glucose tolerance test. The present study is the first to present N-carbamoyl-β-alanine as a potential marker of type 2 diabetes mellitus and consequently to demonstrate the efficacies of the applied antidiabetic interventions. Moreover, the elevated acetate level observed after vildagliptin administration might reflect increased fatty acid oxidation. Copyright © 2016 Elsevier Ireland Ltd. All rights reserved.

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

PubMed

Trushina, Eugenia; Mielke, Michelle M

2014-08-01

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

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

PubMed Central

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

2016-01-01

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

Urine Metabolomics Analysis for Biomarker Discovery and Detection of Jaundice Syndrome in Patients With Liver Disease*

PubMed Central

Wang, Xijun; Zhang, Aihua; Han, Ying; Wang, Ping; Sun, Hui; Song, Gaochen; Dong, Tianwei; Yuan, Ye; Yuan, Xiaoxia; Zhang, Miao; Xie, Ning; Zhang, He; Dong, Hui; Dong, Wei

2012-01-01

Metabolomics is a powerful new technology that allows for the assessment of global metabolic profiles in easily accessible biofluids and biomarker discovery in order to distinguish between diseased and nondiseased status information. Deciphering the molecular networks that distinguish diseases may lead to the identification of critical biomarkers for disease aggressiveness. However, current diagnostic methods cannot predict typical Jaundice syndrome (JS) in patients with liver disease and little is known about the global metabolomic alterations that characterize JS progression. Emerging metabolomics provides a powerful platform for discovering novel biomarkers and biochemical pathways to improve diagnostic, prognostication, and therapy. Therefore, the aim of this study is to find the potential biomarkers from JS disease by using a nontarget metabolomics method, and test their usefulness in human JS diagnosis. Multivariate data analysis methods were utilized to identify the potential biomarkers. Interestingly, 44 marker metabolites contributing to the complete separation of JS from matched healthy controls were identified. Metabolic pathways (Impact-value≥0.10) including alanine, aspartate, and glutamate metabolism and synthesis and degradation of ketone bodies were found to be disturbed in JS patients. This study demonstrates the possibilities of metabolomics as a diagnostic tool in diseases and provides new insight into pathophysiologic mechanisms. PMID:22505723

Investigation of the effect of genotype and agronomic conditions on metabolomic profiles of selected strawberry cultivars with different sensitivity to environmental stress.

PubMed

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

2016-04-01

Strawberry is one of the most economically important and widely cultivated fruit crops across the world, so that there is a growing need to develop new analytical methodologies for the authentication of variety and origin, as well as the assessment of agricultural and processing practices. In this work, an untargeted metabolomic strategy based on gas chromatography mass spectrometry (GC-MS) combined with multivariate statistical techniques was used for the first time to characterize the primary metabolome of different strawberry cultivars and to study metabolite alterations in response to multiple agronomic conditions. For this purpose, we investigated three varieties of strawberries with different sensitivity to environmental stress (Camarosa, Festival and Palomar), cultivated in soilless systems using various electrical conductivities, types of coverage and substrates. Metabolomic analysis revealed significant alterations in primary metabolites between the three strawberry cultivars grown under different crop conditions, including sugars (fructose, glucose), organic acids (malic acid, citric acid) and amino acids (alanine, threonine, aspartic acid), among others. Therefore, it could be concluded that GC-MS based metabolomics is a suitable tool to differentiate strawberry cultivars and characterize metabolomic changes associated with environmental and agronomic conditions. Copyright © 2016 Elsevier Masson SAS. All rights reserved.

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

PubMed

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.

Using silver and bighead carp cell lines for the identification of a unique metabolite fingerprint from thiram-specific chemical exposure

USGS Publications Warehouse

Putnam, Joel G.; Nelson, Justine; Leis, Eric M; Erickson, Richard A.; Hubert, Terrance D.; Amberg, Jon J.

2017-01-01

Conservation biology often requires the control of invasive species. One method is the development and use of biocides. Identifying new chemicals as part of the biocide registration approval process can require screening millions of compounds. Traditionally, screening new chemicals has been done in vivo using test organisms. Using in vitro (e.g., cell lines) and in silico (e.g., computer models) methods decrease test organism requirements and increase screening speed and efficiency. These methods, however, would be greatly improved by better understanding how individual fish species metabolize selected compounds.We combined cell assays and metabolomics to create a powerful tool to facilitate the identification of new control chemicals. Specifically, we exposed cell lines established from bighead carp and silver carp larvae to thiram (7 concentrations) then completed metabolite profiling to assess the dose-response of the bighead carp and silver carp metabolome to thiram. Forty one of the 700 metabolomic markers identified in bighead carp exhibited a dose-response to thiram exposure compared to silver carp in which 205 of 1590 metabolomic markers exhibited a dose-response. Additionally, we identified 11 statistically significant metabolomic markers based upon volcano plot analysis common between both species. This smaller subset of metabolites formed a thiram-specific metabolomic fingerprint which allowed for the creation of a toxicant specific, rather than a species-specific, metabolomic fingerprint. Metabolomic fingerprints may be used in biocide development and improve our understanding of ecologically significant events, such as mass fish kills.

MetaboAnalystR: an R package for flexible and reproducible analysis of metabolomics data.

PubMed

Chong, Jasmine; Xia, Jianguo

2018-06-28

The MetaboAnalyst web application has been widely used for metabolomics data analysis and interpretation. Despite its user-friendliness, the web interface has presented its inherent limitations (especially for advanced users) with regard to flexibility in creating customized workflow, support for reproducible analysis, and capacity in dealing with large data. To address these limitations, we have developed a companion R package (MetaboAnalystR) based on the R code base of the web server. The package has been thoroughly tested to ensure that the same R commands will produce identical results from both interfaces. MetaboAnalystR complements the MetaboAnalyst web server to facilitate transparent, flexible and reproducible analysis of metabolomics data. MetaboAnalystR is freely available from https://github.com/xia-lab/MetaboAnalystR. Supplementary data are available at Bioinformatics online.

In vivo metabolomic interpretation of the anti-obesity effects of hyacinth bean (Dolichos lablab L.) administration in high-fat diet mice.

PubMed

Suh, Dong Ho; Lee, Hye Won; Jung, Eun Sung; Singh, Digar; Kim, Seung-Hyung; Lee, Choong Hwan

2017-08-01

The esoteric anti-obesity effects of hyacinth bean (Dolichos lablab L) have largely remained unexplored. Herein, we investigated the anti-obesity mechanisms of hyacinth bean compared to milk thistle, a natural herb employed for ameliorating obesity-related diseases, using high-fat diet (HFD) fed mice towards unfolding the perplexing mechanisms. C57BL/6J mice were orally administered hyacinth bean (25 mg/kg/day) and milk thistle (100 mg/kg/day) for 9 weeks along with HFD. Intriguingly, a number of anti-obesity mechanisms indexed through clinical parameters, suppression in weight gains and liver steatosis were found similar to some disparity. Furthermore, the corresponding metabolic implications were studied through MS-based metabolite profiling, and using the Kyoto Encyclopedia of Genes and Genomes for metabolic pathways revealing that hyacinth bean or milk thistle administration effectively attenuates the HFD-induced lipid, glucose, and bile acid metabolism, with former specifically attenuates pyruvate-derived amino acids metabolism. Among them, valine, asparagine, and lysine displayed high correlation with blood clinical parameters. A lower dose of hyacinth bean resulted in similar anti-obesity effects as milk thistle, as confirmed by both clinical and metabolomics analyses. Equivocally, we conjecture that hyacinth bean could be used as a potent anti-obesity herbal functional food. © 2017 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Metabolomic Elucidation of the Effects of Curcumin on Fibroblast-Like Synoviocytes in Rheumatoid Arthritis

PubMed Central

Hwang, Jiwon; Kim, Jungyeon; Lee, You Sun; Koh, Eun-Mi; Kim, Kyoung Heon; Cha, Hoon-Suk

2015-01-01

Rheumatoid arthritis (RA) is a chronic systemic inflammatory disease characterized by synovial inflammation and joint disability. Curcumin is known to be effective in ameliorating joint inflammation in RA. To obtain new insights into the effect of curcumin on primary fibroblast-like synoviocytes (FLS, N = 3), which are key effector cells in RA, we employed gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS)-based metabolomics. Metabolomic profiling of tumor necrosis factor (TNF)-α-stimulated and curcumin-treated FLS was performed using GC/TOF-MS in conjunction with univariate and multivariate statistical analyses. A total of 119 metabolites were identified. Metabolomic analysis revealed that metabolite profiles were clearly distinct between TNF-α-stimulated vs. the control group (not stimulated by TNF-α or curcumin). Treatment of FLS with curcumin showed that the metabolic perturbation by TNF-α could be reversed to that of the control group to a considerable extent. Curcumin-treated FLS had higher restoration of amino acid and fatty acid metabolism, as indicated by the prominent metabolic restoration of intermediates of amino acid and fatty acid metabolism, compared with that observed in TNF-α-stimulated FLS. In particular, the abundance of glycine, citrulline, arachidonic acid, and saturated fatty acids in TNF-α-stimulated FLS was restored to the control level after treatment with curcumin, suggesting that the effect of curcumin on preventing joint inflammation may be elucidated with the levels of these metabolites. Our results suggest that GC/TOF-MS-based metabolomic investigation using FLS has the potential for discovering the mechanism of action of curcumin and new targets for therapeutic drugs in RA. PMID:26716989

Metabolomic Elucidation of the Effects of Curcumin on Fibroblast-Like Synoviocytes in Rheumatoid Arthritis.

PubMed

Ahn, Joong Kyong; Kim, Sooah; Hwang, Jiwon; Kim, Jungyeon; Lee, You Sun; Koh, Eun-Mi; Kim, Kyoung Heon; Cha, Hoon-Suk

2015-01-01

Rheumatoid arthritis (RA) is a chronic systemic inflammatory disease characterized by synovial inflammation and joint disability. Curcumin is known to be effective in ameliorating joint inflammation in RA. To obtain new insights into the effect of curcumin on primary fibroblast-like synoviocytes (FLS, N = 3), which are key effector cells in RA, we employed gas chromatography/time-of-flight mass spectrometry (GC/TOF-MS)-based metabolomics. Metabolomic profiling of tumor necrosis factor (TNF)-α-stimulated and curcumin-treated FLS was performed using GC/TOF-MS in conjunction with univariate and multivariate statistical analyses. A total of 119 metabolites were identified. Metabolomic analysis revealed that metabolite profiles were clearly distinct between TNF-α-stimulated vs. the control group (not stimulated by TNF-α or curcumin). Treatment of FLS with curcumin showed that the metabolic perturbation by TNF-α could be reversed to that of the control group to a considerable extent. Curcumin-treated FLS had higher restoration of amino acid and fatty acid metabolism, as indicated by the prominent metabolic restoration of intermediates of amino acid and fatty acid metabolism, compared with that observed in TNF-α-stimulated FLS. In particular, the abundance of glycine, citrulline, arachidonic acid, and saturated fatty acids in TNF-α-stimulated FLS was restored to the control level after treatment with curcumin, suggesting that the effect of curcumin on preventing joint inflammation may be elucidated with the levels of these metabolites. Our results suggest that GC/TOF-MS-based metabolomic investigation using FLS has the potential for discovering the mechanism of action of curcumin and new targets for therapeutic drugs in RA.

Heritable IUGR and adult metabolic syndrome are reversible and associated with alterations in the metabolome following dietary supplementation of 1-carbon intermediates.

PubMed

Seferovic, Maxim D; Goodspeed, Danielle M; Chu, Derrick M; Krannich, Laura A; Gonzalez-Rodriguez, Pablo J; Cox, James E; Aagaard, Kjersti M

2015-06-01

Metabolic syndrome (MetS), following intrauterine growth restriction (IUGR), is epigenetically heritable. Recently, we abrogated the F2 adult phenotype with essential nutrient supplementation (ENS) of intermediates along the 1-carbon pathway. With the use of the same grandparental uterine artery ligation model, we profiled the F2 serum metabolome at weaning [postnatal day (d)21; n = 76] and adulthood (d160; n = 12) to test if MetS is preceded by alterations in the metabolome. Indicative of developmentally programmed MetS, adult F2, formerly IUGR rats, were obese (621 vs. 461 g; P < 0.0001), dyslipidemic (133 vs. 67 mg/dl; P < 0.001), and glucose intolerant (26 vs. 15 mg/kg/min; P < 0.01). Unbiased gas chromatography-mass spectrometry (GC-MS) profiling revealed 34 peaks corresponding to 12 nonredundant metabolites and 9 unknowns to be changing at weaning [false discovery rate (FDR) < 0.05]. Markers of later-in-life MetS included citric acid, glucosamine, myoinositol, and proline (P < 0.03). Hierarchical clustering revealed grouping by IUGR lineage and supplementation at d21 and d160. Weanlings grouped distinctly for ENS and IUGR by partial least-squares discriminate analysis (PLS-DA; P < 0.01), whereas paternal and maternal IUGR (IUGR(pat)/IUGR(mat), respectively) control-fed rats, destined for MetS, had a distinct metabolome at weaning (randomForest analysis; class error < 0.1) and adulthood (PLS-DA; P < 0.05). In sum, we have found that alterations in the metabolome accompany heritable IUGR, precede adult-onset MetS, and are partially amenable to dietary intervention. © FASEB.

Extending metabolome coverage for untargeted metabolite profiling of adherent cultured hepatic cells.

PubMed

García-Cañaveras, Juan Carlos; López, Silvia; Castell, José Vicente; Donato, M Teresa; Lahoz, Agustín

2016-02-01

MS-based metabolite profiling of adherent mammalian cells comprises several challenging steps such as metabolism quenching, cell detachment, cell disruption, metabolome extraction, and metabolite measurement. In LC-MS, the final metabolome coverage is strongly determined by the separation technique and the MS conditions used. Human liver-derived cell line HepG2 was chosen as adherent mammalian cell model to evaluate the performance of several commonly used procedures in both sample processing and LC-MS analysis. In a first phase, metabolite extraction and sample analysis were optimized in a combined manner. To this end, the extraction abilities of five different solvents (or combinations) were assessed by comparing the number and the levels of the metabolites comprised in each extract. Three different chromatographic methods were selected for metabolites separation. A HILIC-based method which was set to specifically separate polar metabolites and two RP-based methods focused on lipidome and wide-ranging metabolite detection, respectively. With regard to metabolite measurement, a Q-ToF instrument operating in both ESI (+) and ESI (-) was used for unbiased extract analysis. Once metabolite extraction and analysis conditions were set up, the influence of cell harvesting on metabolome coverage was also evaluated. Therefore, different protocols for cell detachment (trypsinization or scraping) and metabolism quenching were compared. This study confirmed the inconvenience of trypsinization as a harvesting technique, and the importance of using complementary extraction solvents to extend metabolome coverage, minimizing interferences and maximizing detection, thanks to the use of dedicated analytical conditions through the combination of HILIC and RP separations. The proposed workflow allowed the detection of over 300 identified metabolites from highly polar compounds to a wide range of lipids.

Two complementary reversed-phase separations for comprehensive coverage of the semipolar and nonpolar metabolome.

PubMed

Naser, Fuad J; Mahieu, Nathaniel G; Wang, Lingjue; Spalding, Jonathan L; Johnson, Stephen L; Patti, Gary J

2018-02-01

Although it is common in untargeted metabolomics to apply reversed-phase liquid chromatography (RPLC) and hydrophilic interaction liquid chromatography (HILIC) methods that have been systematically optimized for lipids and central carbon metabolites, here we show that these established protocols provide poor coverage of semipolar metabolites because of inadequate retention. Our objective was to develop an RPLC approach that improved detection of these metabolites without sacrificing lipid coverage. We initially evaluated columns recently released by Waters under the CORTECS line by analyzing 47 small-molecule standards that evenly span the nonpolar and semipolar ranges. An RPLC method commonly used in untargeted metabolomics was considered a benchmarking reference. We found that highly nonpolar and semipolar metabolites cannot be reliably profiled with any single method because of retention and solubility limitations of the injection solvent. Instead, we optimized a multiplexed approach using the CORTECS T3 column to analyze semipolar compounds and the CORTECS C 8 column to analyze lipids. Strikingly, we determined that combining these methods allowed detection of 41 of the total 47 standards, whereas our reference RPLC method detected only 10 of the 47 standards. We then applied credentialing to compare method performance at the comprehensive scale. The tandem method showed more than a fivefold increase in credentialing coverage relative to our RPLC benchmark. Our results demonstrate that comprehensive coverage of metabolites amenable to reversed-phase separation necessitates two reconstitution solvents and chromatographic methods. Thus, we suggest complementing HILIC methods with a dual T3 and C 8 RPLC approach to increase coverage of semipolar metabolites and lipids for untargeted metabolomics. Graphical abstract Analysis of semipolar and nonpolar metabolites necessitates two reversed-phase chromatography (RPLC) methods, which extend metabolome coverage more than fivefold for untargeted profiling. HILIC hydrophilic interaction liquid chromatography.

Metabolomic characterization of laborers exposed to welding fumes.

PubMed

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

2012-03-19

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

The Same Microbiota and a Potentially Discriminant Metabolome in the Saliva of Omnivore, Ovo-Lacto-Vegetarian and Vegan Individuals

PubMed Central

De Filippis, Francesca; Vannini, Lucia; La Storia, Antonietta; Laghi, Luca; Piombino, Paola; Stellato, Giuseppina; Serrazanetti, Diana I.; Gozzi, Giorgia; Turroni, Silvia; Ferrocino, Ilario; Lazzi, Camilla; Di Cagno, Raffaella; Gobbetti, Marco; Ercolini, Danilo

2014-01-01

The salivary microbiota has been linked to both oral and non-oral diseases. Scant knowledge is available on the effect of environmental factors such as long-term dietary choices on the salivary microbiota and metabolome. This study analyzed the microbial diversity and metabolomic profiles of the saliva of 161 healthy individuals who followed an omnivore or ovo-lacto-vegetarian or vegan diet. A large core microbiota was identified, including 12 bacterial genera, found in >98% of the individuals. The subjects could be stratified into three “salivary types” that differed on the basis of the relative abundance of the core genera Prevotella, Streptococcus/Gemella and Fusobacterium/Neisseria. Statistical analysis indicated no effect of dietary habit on the salivary microbiota. Phylogenetic beta-diversity analysis consistently showed no differences between omnivore, ovo-lacto-vegetarian and vegan individuals. Metabolomic profiling of saliva using 1H-NMR and GC-MS/SPME identified diet-related biomarkers that enabled a significant discrimination between the 3 groups of individuals on the basis of their diet. Formate, urea, uridine and 5-methyl-3-hexanone could discriminate samples from omnivores, whereas 1-propanol, hexanoic acid and proline were characteristic of non-omnivore diets. Although the salivary metabolome can be discriminating for diet, the microbiota has a remarkable inter-individual stability and did not vary with dietary habits. Microbial homeostasis might be perturbed with sub-standard oral hygiene or other environmental factors, but there is no current indication that a choice of an omnivore, ovo-lacto-vegetarian or vegan diet can lead to a specific composition of the oral microbiota with consequences on the oral homeostasis. PMID:25372853

The same microbiota and a potentially discriminant metabolome in the saliva of omnivore, ovo-lacto-vegetarian and Vegan individuals.

PubMed

De Filippis, Francesca; Vannini, Lucia; La Storia, Antonietta; Laghi, Luca; Piombino, Paola; Stellato, Giuseppina; Serrazanetti, Diana I; Gozzi, Giorgia; Turroni, Silvia; Ferrocino, Ilario; Lazzi, Camilla; Di Cagno, Raffaella; Gobbetti, Marco; Ercolini, Danilo

2014-01-01

The salivary microbiota has been linked to both oral and non-oral diseases. Scant knowledge is available on the effect of environmental factors such as long-term dietary choices on the salivary microbiota and metabolome. This study analyzed the microbial diversity and metabolomic profiles of the saliva of 161 healthy individuals who followed an omnivore or ovo-lacto-vegetarian or vegan diet. A large core microbiota was identified, including 12 bacterial genera, found in >98% of the individuals. The subjects could be stratified into three "salivary types" that differed on the basis of the relative abundance of the core genera Prevotella, Streptococcus/Gemella and Fusobacterium/Neisseria. Statistical analysis indicated no effect of dietary habit on the salivary microbiota. Phylogenetic beta-diversity analysis consistently showed no differences between omnivore, ovo-lacto-vegetarian and vegan individuals. Metabolomic profiling of saliva using (1)H-NMR and GC-MS/SPME identified diet-related biomarkers that enabled a significant discrimination between the 3 groups of individuals on the basis of their diet. Formate, urea, uridine and 5-methyl-3-hexanone could discriminate samples from omnivores, whereas 1-propanol, hexanoic acid and proline were characteristic of non-omnivore diets. Although the salivary metabolome can be discriminating for diet, the microbiota has a remarkable inter-individual stability and did not vary with dietary habits. Microbial homeostasis might be perturbed with sub-standard oral hygiene or other environmental factors, but there is no current indication that a choice of an omnivore, ovo-lacto-vegetarian or vegan diet can lead to a specific composition of the oral microbiota with consequences on the oral homeostasis.

Metabolomic profiles in individuals with negative affectivity and social inhibition: a population-based study of Type D personality.

PubMed

Altmaier, Elisabeth; Emeny, Rebecca T; Krumsiek, Jan; Lacruz, Maria E; Lukaschek, Karoline; Häfner, Sibylle; Kastenmüller, Gabi; Römisch-Margl, Werner; Prehn, Cornelia; Mohney, Robert P; Evans, Anne M; Milburn, Michael V; Illig, Thomas; Adamski, Jerzy; Theis, Fabian; Suhre, Karsten; Ladwig, Karl-Heinz

2013-08-01

Individuals with negative affectivity who are inhibited in social situations are characterized as distressed, or Type D, and have an increased risk of cardiovascular disease (CVD). The underlying biomechanisms that link this psychological affect to a pathological state are not well understood. This study applied a metabolomic approach to explore biochemical pathways that may contribute to the Type D personality. Type D personality was determined by the Type D Scale-14. Small molecule biochemicals were measured using two complementary mass-spectrometry based metabolomics platforms. Metabolic profiles of Type D and non-Type D participants within a population-based study in Southern Germany were compared in cross-sectional regression analyses. The PHQ-9 and GAD-7 instruments were also used to assess symptoms of depression and anxiety, respectively, within this metabolomic study. 668 metabolites were identified in the serum of 1502 participants (age 32-77); 386 of these individuals were classified as Type D. While demographic and biomedical characteristics were equally distributed between the groups, a higher level of depression and anxiety was observed in Type D individuals. Significantly lower levels of the tryptophan metabolite kynurenine were associated with Type D (p-value corrected for multiple testing=0.042), while no significant associations could be found for depression and anxiety. A Gaussian graphical model analysis enabled the identification of four potentially interesting metabolite networks that are enriched in metabolites (androsterone sulfate, tyrosine, indoxyl sulfate or caffeine) that associate nominally with Type D personality. This study identified novel biochemical pathways associated with Type D personality and demonstrates that the application of metabolomic approaches in population studies can reveal mechanisms that may contribute to psychological health and disease. Copyright © 2012 Elsevier Ltd. All rights reserved.

All roads lead to Rome: Towards understanding different avenues of tolerance to huanglongbing in citrus cultivars.

PubMed

Killiny, Nabil; Jones, Shelley E; Nehela, Yasser; Hijaz, Faraj; Dutt, Manjul; Gmitter, Frederick G; Grosser, Jude W

2018-05-18

Citrus tolerance to huanglongbing could result from tolerance to the pathogen Candidatus Liberibacter asiaticus (CLas) and/or to its vector Diaphorina citri. Field observations and greenhouse-controlled studies showed that some citrus cultivars were more tolerant than others. However, the mechanism(s) behind the tolerance has not been determined yet. Using GC-MS, we investigated the volatile organic compounds (VOCs) and the non-volatile metabolite profiles of two tolerant citrus cultivars- Australian finger lime, 'LB8-9' Sugar Belle ® mandarin hybrid, and a recently released mandarin hybrid 'Bingo'. The three were grafted onto the rootstock, Carrizo citrange. Our findings showed that the metabolomic profiles of Australian finger lime were different from that of 'LB8-9'. Finger lime was high in many amino acids and tricarboxylic acid intermediates, whereas 'LB8-9' was high in several amino acids, sugars, and sugar alcohols. 'LB8-9' was high in thymol, which is known for its strong antimicrobial activity against a panel of pathogenic bacteria. The metabolomic profiles of 'Bingo' were intensely different from the other mandarin hybrid, 'LB8-9', including a reduced thymol biosynthetic pathway and low amounts of most of the amino acids and sugar alcohols. Remarkably, 1,8-cineole (eucalyptol) was only detected in 'Bingo', indicating that eucalyptol could have feeding and ovipositional repellency against D. citri. The metabolite profiles generated for HLB-tolerant citrus species will improve the ability of citrus breeders and will allow them to take more informed decisions. Metabolomic profiling of HLB-tolerant citrus species could identify tolerance specific markers that can be introduced to other commercial citrus cultivars to improve their tolerance to HLB disease. Copyright © 2018 Elsevier Masson SAS. All rights reserved.

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

DOE PAGES

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

2017-04-07

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

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

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

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

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

Partial Least Squares with Structured Output for Modelling the Metabolomics Data Obtained from Complex Experimental Designs: A Study into the Y-Block Coding.

PubMed

Xu, Yun; Muhamadali, Howbeer; Sayqal, Ali; Dixon, Neil; Goodacre, Royston

2016-10-28

Partial least squares (PLS) is one of the most commonly used supervised modelling approaches for analysing multivariate metabolomics data. PLS is typically employed as either a regression model (PLS-R) or a classification model (PLS-DA). However, in metabolomics studies it is common to investigate multiple, potentially interacting, factors simultaneously following a specific experimental design. Such data often cannot be considered as a "pure" regression or a classification problem. Nevertheless, these data have often still been treated as a regression or classification problem and this could lead to ambiguous results. In this study, we investigated the feasibility of designing a hybrid target matrix Y that better reflects the experimental design than simple regression or binary class membership coding commonly used in PLS modelling. The new design of Y coding was based on the same principle used by structural modelling in machine learning techniques. Two real metabolomics datasets were used as examples to illustrate how the new Y coding can improve the interpretability of the PLS model compared to classic regression/classification coding.

Comprehensive evaluation of untargeted metabolomics data processing software in feature detection, quantification and discriminating marker selection.

PubMed

Li, Zhucui; Lu, Yan; Guo, Yufeng; Cao, Haijie; Wang, Qinhong; Shui, Wenqing

2018-10-31

Data analysis represents a key challenge for untargeted metabolomics studies and it commonly requires extensive processing of more than thousands of metabolite peaks included in raw high-resolution MS data. Although a number of software packages have been developed to facilitate untargeted data processing, they have not been comprehensively scrutinized in the capability of feature detection, quantification and marker selection using a well-defined benchmark sample set. In this study, we acquired a benchmark dataset from standard mixtures consisting of 1100 compounds with specified concentration ratios including 130 compounds with significant variation of concentrations. Five software evaluated here (MS-Dial, MZmine 2, XCMS, MarkerView, and Compound Discoverer) showed similar performance in detection of true features derived from compounds in the mixtures. However, significant differences between untargeted metabolomics software were observed in relative quantification of true features in the benchmark dataset. MZmine 2 outperformed the other software in terms of quantification accuracy and it reported the most true discriminating markers together with the fewest false markers. Furthermore, we assessed selection of discriminating markers by different software using both the benchmark dataset and a real-case metabolomics dataset to propose combined usage of two software for increasing confidence of biomarker identification. Our findings from comprehensive evaluation of untargeted metabolomics software would help guide future improvements of these widely used bioinformatics tools and enable users to properly interpret their metabolomics results. Copyright © 2018 Elsevier B.V. All rights reserved.

Metabolomics method to comprehensively analyze amino acids in different domains.

PubMed

Gu, Haiwei; Du, Jianhai; Carnevale Neto, Fausto; Carroll, Patrick A; Turner, Sally J; Chiorean, E Gabriela; Eisenman, Robert N; Raftery, Daniel

2015-04-21

Amino acids play essential roles in both metabolism and the proteome. Many studies have profiled free amino acids (FAAs) or proteins; however, few have connected the measurement of FAA with individual amino acids in the proteome. In this study, we developed a metabolomics method to comprehensively analyze amino acids in different domains, using two examples of different sample types and disease models. We first examined the responses of FAAs and insoluble-proteome amino acids (IPAAs) to the Myc oncogene in Tet21N human neuroblastoma cells. The metabolic and proteomic amino acid profiles were quite different, even under the same Myc condition, and their combination provided a better understanding of the biological status. In addition, amino acids were measured in 3 domains (FAAs, free and soluble-proteome amino acids (FSPAAs), and IPAAs) to study changes in serum amino acid profiles related to colon cancer. A penalized logistic regression model based on the amino acids from the three domains had better sensitivity and specificity than that from each individual domain. To the best of our knowledge, this is the first study to perform a combined analysis of amino acids in different domains, and indicates the useful biological information available from a metabolomics analysis of the protein pellet. This study lays the foundation for further quantitative tracking of the distribution of amino acids in different domains, with opportunities for better diagnosis and mechanistic studies of various diseases.

Global metabolic analyses identify key differences in metabolite levels between polymyxin-susceptible and polymyxin-resistant Acinetobacter baumannii

PubMed Central

Mahamad Maifiah, Mohd Hafidz; Cheah, Soon-Ee; Johnson, Matthew D.; Han, Mei-Ling; Boyce, John D.; Thamlikitkul, Visanu; Forrest, Alan; Kaye, Keith S.; Hertzog, Paul; Purcell, Anthony W.; Song, Jiangning; Velkov, Tony; Creek, Darren J.; Li, Jian

2016-01-01

Multidrug-resistant Acinetobacter baumannii presents a global medical crisis and polymyxins are used as the last-line therapy. This study aimed to identify metabolic differences between polymyxin-susceptible and polymyxin-resistant A. baumannii using untargeted metabolomics. The metabolome of each A. baumannii strain was measured using liquid chromatography-mass spectrometry. Multivariate and univariate statistics and pathway analyses were employed to elucidate metabolic differences between the polymyxin-susceptible and -resistant A. baumannii strains. Significant differences were identified between the metabolic profiles of the polymyxin-susceptible and -resistant A. baumannii strains. The lipopolysaccharide (LPS) deficient, polymyxin-resistant 19606R showed perturbation in specific amino acid and carbohydrate metabolites, particularly pentose phosphate pathway (PPP) and tricarboxylic acid (TCA) cycle intermediates. Levels of nucleotides were lower in the LPS-deficient 19606R. Furthermore, 19606R exhibited a shift in its glycerophospholipid profile towards increased abundance of short-chain lipids compared to the parent polymyxin-susceptible ATCC 19606. In contrast, in a pair of clinical isolates 03–149.1 (polymyxin-susceptible) and 03–149.2 (polymyxin-resistant, due to modification of lipid A), minor metabolic differences were identified. Notably, peptidoglycan biosynthesis metabolites were significantly depleted in both of the aforementioned polymyxin-resistant strains. This is the first comparative untargeted metabolomics study to show substantial differences in the metabolic profiles of the polymyxin-susceptible and -resistant A. baumannii. PMID:26924392

Global metabolic analyses identify key differences in metabolite levels between polymyxin-susceptible and polymyxin-resistant Acinetobacter baumannii.

PubMed

Maifiah, Mohd Hafidz Mahamad; Cheah, Soon-Ee; Johnson, Matthew D; Han, Mei-Ling; Boyce, John D; Thamlikitkul, Visanu; Forrest, Alan; Kaye, Keith S; Hertzog, Paul; Purcell, Anthony W; Song, Jiangning; Velkov, Tony; Creek, Darren J; Li, Jian

2016-02-29

Multidrug-resistant Acinetobacter baumannii presents a global medical crisis and polymyxins are used as the last-line therapy. This study aimed to identify metabolic differences between polymyxin-susceptible and polymyxin-resistant A. baumannii using untargeted metabolomics. The metabolome of each A. baumannii strain was measured using liquid chromatography-mass spectrometry. Multivariate and univariate statistics and pathway analyses were employed to elucidate metabolic differences between the polymyxin-susceptible and -resistant A. baumannii strains. Significant differences were identified between the metabolic profiles of the polymyxin-susceptible and -resistant A. baumannii strains. The lipopolysaccharide (LPS) deficient, polymyxin-resistant 19606R showed perturbation in specific amino acid and carbohydrate metabolites, particularly pentose phosphate pathway (PPP) and tricarboxylic acid (TCA) cycle intermediates. Levels of nucleotides were lower in the LPS-deficient 19606R. Furthermore, 19606R exhibited a shift in its glycerophospholipid profile towards increased abundance of short-chain lipids compared to the parent polymyxin-susceptible ATCC 19606. In contrast, in a pair of clinical isolates 03-149.1 (polymyxin-susceptible) and 03-149.2 (polymyxin-resistant, due to modification of lipid A), minor metabolic differences were identified. Notably, peptidoglycan biosynthesis metabolites were significantly depleted in both of the aforementioned polymyxin-resistant strains. This is the first comparative untargeted metabolomics study to show substantial differences in the metabolic profiles of the polymyxin-susceptible and -resistant A. baumannii.

Predictive toxicology using systemic biology and liver microfluidic “on chip” approaches: Application to acetaminophen injury

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

Prot, Jean-Matthieu; Bunescu, Andrei; Elena-Herrmann, Bénédicte

2012-03-15

We have analyzed transcriptomic, proteomic and metabolomic profiles of hepatoma cells cultivated inside a microfluidic biochip with or without acetaminophen (APAP). Without APAP, the results show an adaptive cellular response to the microfluidic environment, leading to the induction of anti-oxidative stress and cytoprotective pathways. In presence of APAP, calcium homeostasis perturbation, lipid peroxidation and cell death are observed. These effects can be attributed to APAP metabolism into its highly reactive metabolite, N-acetyl-p-benzoquinone imine (NAPQI). That toxicity pathway was confirmed by the detection of GSH-APAP, the large production of 2-hydroxybutyrate and 3-hydroxybutyrate, and methionine, cystine, and histidine consumption in the treatedmore » biochips. Those metabolites have been reported as specific biomarkers of hepatotoxicity and glutathione depletion in the literature. In addition, the integration of the metabolomic, transcriptomic and proteomic collected profiles allowed a more complete reconstruction of the APAP injury pathways. To our knowledge, this work is the first example of a global integration of microfluidic biochip data in toxicity assessment. Our results demonstrate the potential of that new approach to predictive toxicology. -- Highlights: ► We cultivated liver cells in microfluidic biochips ► We integrated transcriptomic, proteomic and metabolomics profiles ► Pathways reconstructions were proposed in control and acetaminophen treated cultures ► Biomarkers were identified ► Comparisons with in vivo studies were proposed.« less

Using Metabolomic Profiles as Biomarkers for Insulin Resistance in Childhood Obesity: A Systematic Review.

PubMed

Zhao, Xue; Gang, Xiaokun; Liu, Yujia; Sun, Chenglin; Han, Qing; Wang, Guixia

2016-01-01

A growing body of evidence has shown the intimate relationship between metabolomic profiles and insulin resistance (IR) in obese adults, while little is known about childhood obesity. In this review, we searched available papers addressing metabolomic profiles and IR in obese children from inception to February 2016 on MEDLINE, Web of Science, the Cochrane Library, ClinicalTrials.gov, and EMASE. HOMA-IR was applied as surrogate markers of IR and related metabolic disorders at both baseline and follow-up. To minimize selection bias, two investigators independently completed this work. After critical selection, 10 studies (including 2,673 participants) were eligible and evaluated by using QUADOMICS for quality assessment. Six of the 10 studies were classified as "high quality." Then we generated all the metabolites identified in each study and found amino acid metabolism and lipid metabolism were the main affected metabolic pathways in obese children. Among identified metabolites, branched-chain amino acids (BCAAs), aromatic amino acids (AAAs), and acylcarnitines were reported to be associated with IR as biomarkers most frequently. Additionally, BCAAs and tyrosine seemed to be relevant to future metabolic risk in the long-term follow-up cohorts, emphasizing the importance of early diagnosis and prevention strategy. Because of limited scale and design heterogeneity of existing studies, future studies might focus on validating above findings in more large-scale and longitudinal studies with elaborate design.

Experimental Chagas disease-induced perturbations of the fecal microbiome and metabolome.

PubMed

McCall, Laura-Isobel; Tripathi, Anupriya; Vargas, Fernando; Knight, Rob; Dorrestein, Pieter C; Siqueira-Neto, Jair L

2018-03-01

Trypanosoma cruzi parasites are the causative agents of Chagas disease. These parasites infect cardiac and gastrointestinal tissues, leading to local inflammation and tissue damage. Digestive Chagas disease is associated with perturbations in food absorption, intestinal traffic and defecation. However, the impact of T. cruzi infection on the gut microbiota and metabolome have yet to be characterized. In this study, we applied mass spectrometry-based metabolomics and 16S rRNA sequencing to profile infection-associated alterations in fecal bacterial composition and fecal metabolome through the acute-stage and into the chronic stage of infection, in a murine model of Chagas disease. We observed joint microbial and chemical perturbations associated with T. cruzi infection. These included alterations in conjugated linoleic acid (CLA) derivatives and in specific members of families Ruminococcaceae and Lachnospiraceae, as well as alterations in secondary bile acids and members of order Clostridiales. These results highlight the importance of multi-'omics' and poly-microbial studies in understanding parasitic diseases in general, and Chagas disease in particular.

Modelling short time series in metabolomics: a functional data analysis approach.

PubMed

Montana, Giovanni; Berk, Maurice; Ebbels, Tim

2011-01-01

Metabolomics is the study of the complement of small molecule metabolites in cells, biofluids and tissues. Many metabolomic experiments are designed to compare changes observed over time under two or more experimental conditions (e.g. a control and drug-treated group), thus producing time course data. Models from traditional time series analysis are often unsuitable because, by design, only very few time points are available and there are a high number of missing values. We propose a functional data analysis approach for modelling short time series arising in metabolomic studies which overcomes these obstacles. Our model assumes that each observed time series is a smooth random curve, and we propose a statistical approach for inferring this curve from repeated measurements taken on the experimental units. A test statistic for detecting differences between temporal profiles associated with two experimental conditions is then presented. The methodology has been applied to NMR spectroscopy data collected in a pre-clinical toxicology study.

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

PubMed

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.

Metabolome progression during early gut microbial colonization of gnotobiotic mice

PubMed Central

Marcobal, Angela; Yusufaly, Tahir; Higginbottom, Steven; Snyder, Michael; Sonnenburg, Justin L.; Mias, George I.

2015-01-01

The microbiome has been implicated directly in host health, especially host metabolic processes and development of immune responses. These are particularly important in infants where the gut first begins being colonized, and such processes may be modeled in mice. In this investigation we follow longitudinally the urine metabolome of ex-germ-free mice, which are colonized with two bacterial species, Bacteroides thetaiotaomicron and Bifidobacterium longum. High-throughput mass spectrometry profiling of urine samples revealed dynamic changes in the metabolome makeup, associated with the gut bacterial colonization, enabled by our adaptation of non-linear time-series analysis to urine metabolomics data. Results demonstrate both gradual and punctuated changes in metabolite production and that early colonization events profoundly impact the nature of small molecules circulating in the host. The identified small molecules are implicated in amino acid and carbohydrate metabolic processes, and offer insights into the dynamic changes occurring during the colonization process, using high-throughput longitudinal methodology. PMID:26118551

Metabolomics fingerprint of coffee species determined by untargeted-profiling study using LC-HRMS.

PubMed

Souard, Florence; Delporte, Cédric; Stoffelen, Piet; Thévenot, Etienne A; Noret, Nausicaa; Dauvergne, Bastien; Kauffmann, Jean-Michel; Van Antwerpen, Pierre; Stévigny, Caroline

2018-04-15

Coffee bean extracts are consumed all over the world as beverage and there is a growing interest in coffee leaf extracts as food supplements. The wild diversity in Coffea (Rubiaceae) genus is large and could offer new opportunities and challenges. In the present work, a metabolomics approach was implemented to examine leaf chemical composition of 9 Coffea species grown in the same environmental conditions. Leaves were analyzed by LC-HRMS and a comprehensive statistical workflow was designed. It served for univariate hypothesis testing and multivariate modeling by PCA and partial PLS-DA on the Workflow4Metabolomics infrastructure. The first two axes of PCA and PLS-DA describes more than 40% of variances with good values of explained variances. This strategy permitted to investigate the metabolomics data and their relation with botanic and genetic informations. Finally, the identification of several key metabolites for the discrimination between species was further characterized. Copyright © 2017 Elsevier Ltd. All rights reserved.

Effect of environment and genotype on commercial maize hybrids using LC/MS-based metabolomics.

PubMed

Baniasadi, Hamid; Vlahakis, Chris; Hazebroek, Jan; Zhong, Cathy; Asiago, Vincent

2014-02-12

We recently applied gas chromatography coupled to time-of-flight mass spectrometry (GC/TOF-MS) and multivariate statistical analysis to measure biological variation of many metabolites due to environment and genotype in forage and grain samples collected from 50 genetically diverse nongenetically modified (non-GM) DuPont Pioneer commercial maize hybrids grown at six North American locations. In the present study, the metabolome coverage was extended using a core subset of these grain and forage samples employing ultra high pressure liquid chromatography (uHPLC) mass spectrometry (LC/MS). A total of 286 and 857 metabolites were detected in grain and forage samples, respectively, using LC/MS. Multivariate statistical analysis was utilized to compare and correlate the metabolite profiles. Environment had a greater effect on the metabolome than genetic background. The results of this study support and extend previously published insights into the environmental and genetic associated perturbations to the metabolome that are not associated with transgenic modification.

A metabolomics guided exploration of marine natural product chemical space.

PubMed

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

2016-09-01

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

Comparative metabolomics of aging in a long-lived bat: Insights into the physiology of extreme longevity

PubMed Central

levari-Shariati, Shiva; Cooper, Lisa Noelle; Aliani, Michel

2018-01-01

Vespertilionid bats (Mammalia: Order Chiroptera) live 3–10 times longer than other mammals of an equivalent body size. At present, nothing is known of how bat fecal metabolic profiles shift with age in any taxa. This study established the feasibility of using a non-invasive, fecal metabolomics approach to examine age-related differences in the fecal metabolome of young and elderly adult big brown bats (Eptesicus fuscus) as an initial investigation into using metabolomics for age determination. Samples were collected from captive, known-aged big brown bats (Eptesicus fuscus) from 1 to over 14 years of age: these two ages represent age groups separated by approximately 75% of the known natural lifespan of this taxon. Results showed 41 metabolites differentiated young (n = 22) and elderly (n = 6) Eptesicus. Significant differences in metabolites between young and elderly bats were associated with tryptophan metabolism and incomplete protein digestion. Results support further exploration of the physiological mechanisms bats employ to achieve exceptional longevity. PMID:29715267

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

PubMed

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

2018-01-01

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

Comprehensive untargeted metabolomics of Lychnnophorinae subtribe (Asteraceae: Vernonieae) in a phylogenetic context.

PubMed

Martucci, Maria Elvira Poleti; Loeuille, Benoit; Pirani, José Rubens; Gobbo-Neto, Leonardo

2018-01-01

Members of the subtribe Lychnophorinae occur mostly within the Cerrado domain of the Brazilian Central Plateau. The relationships between its 11 genera, as well as between Lychnophorinae and other subtribes belonging to the tribe Vernonieae, have recently been investigated upon a phylogeny based on molecular and morphological data. We report the use of a comprehensive untargeted metabolomics approach, combining HPLC-MS and GC-MS data, followed by multivariate analyses aiming to assess the congruence between metabolomics data and the phylogenetic hypothesis, as well as its potential as a chemotaxonomic tool. We analyzed 78 species by UHPLC-MS and GC-MS in both positive and negative ionization modes. The metabolic profiles obtained for these species were treated in MetAlign and in MSClust and the matrices generated were used in SIMCA for hierarchical cluster analyses, principal component analyses and orthogonal partial least square discriminant analysis. The results showed that metabolomic analyses are mostly congruent with the phylogenetic hypothesis especially at lower taxonomic levels (Lychnophora or Eremanthus). Our results confirm that data generated using metabolomics provide evidence for chemotaxonomical studies, especially for phylogenetic inference of the Lychnophorinae subtribe and insight into the evolution of the secondary metabolites of this group.

Comprehensive untargeted metabolomics of Lychnnophorinae subtribe (Asteraceae: Vernonieae) in a phylogenetic context

PubMed Central

Martucci, Maria Elvira Poleti; Loeuille, Benoit; Pirani, José Rubens

2018-01-01

Members of the subtribe Lychnophorinae occur mostly within the Cerrado domain of the Brazilian Central Plateau. The relationships between its 11 genera, as well as between Lychnophorinae and other subtribes belonging to the tribe Vernonieae, have recently been investigated upon a phylogeny based on molecular and morphological data. We report the use of a comprehensive untargeted metabolomics approach, combining HPLC-MS and GC-MS data, followed by multivariate analyses aiming to assess the congruence between metabolomics data and the phylogenetic hypothesis, as well as its potential as a chemotaxonomic tool. We analyzed 78 species by UHPLC-MS and GC-MS in both positive and negative ionization modes. The metabolic profiles obtained for these species were treated in MetAlign and in MSClust and the matrices generated were used in SIMCA for hierarchical cluster analyses, principal component analyses and orthogonal partial least square discriminant analysis. The results showed that metabolomic analyses are mostly congruent with the phylogenetic hypothesis especially at lower taxonomic levels (Lychnophora or Eremanthus). Our results confirm that data generated using metabolomics provide evidence for chemotaxonomical studies, especially for phylogenetic inference of the Lychnophorinae subtribe and insight into the evolution of the secondary metabolites of this group. PMID:29324799

Relationships between digestive efficiency and metabolomic profiles of serum and intestinal contents in chickens.

PubMed

Beauclercq, Stéphane; Nadal-Desbarats, Lydie; Hennequet-Antier, Christelle; Gabriel, Irène; Tesseraud, Sophie; Calenge, Fanny; Le Bihan-Duval, Elisabeth; Mignon-Grasteau, Sandrine

2018-04-27

The increasing cost of conventional feedstuffs has bolstered interest in genetic selection for digestive efficiency (DE), a component of feed efficiency, assessed by apparent metabolisable energy corrected to zero nitrogen retention (AMEn). However, its measurement is time-consuming and constraining, and its relationship with metabolic efficiency poorly understood. To simplify selection for this trait, we searched for indirect metabolic biomarkers through an analysis of the serum metabolome using nuclear magnetic resonance ( 1 H NMR). A partial least squares (PLS) model including six amino acids and two derivatives from butyrate predicted 59% of AMEn variability. Moreover, to increase our knowledge of the molecular mechanisms controlling DE, we investigated 1 H NMR metabolomes of ileal, caecal, and serum contents by fitting canonical sparse PLS. This analysis revealed strong associations between metabolites and DE. Models based on the ileal, caecal, and serum metabolome respectively explained 77%, 78%, and 74% of the variability of AMEn and its constitutive components (utilisation of starch, lipids, and nitrogen). In our conditions, the metabolites presenting the strongest associations with AMEn were proline in the serum, fumarate in the ileum and glucose in caeca. This study shows that serum metabolomics offers new opportunities to predict chicken DE.

Brain Injury Alters Volatile Metabolome

PubMed Central

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

2016-01-01

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

Metabolomics for Plant Improvement: Status and Prospects

PubMed Central

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

2017-01-01

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

Untargeted UPLC-MS Profiling Pipeline to Expand Tissue Metabolome Coverage: Application to Cardiovascular Disease

PubMed Central

2015-01-01

Metabolic profiling studies aim to achieve broad metabolome coverage in specific biological samples. However, wide metabolome coverage has proven difficult to achieve, mostly because of the diverse physicochemical properties of small molecules, obligating analysts to seek multiplatform and multimethod approaches. Challenges are even greater when it comes to applications to tissue samples, where tissue lysis and metabolite extraction can induce significant systematic variation in composition. We have developed a pipeline for obtaining the aqueous and organic compounds from diseased arterial tissue using two consecutive extractions, followed by a different untargeted UPLC-MS analysis method for each extract. Methods were rationally chosen and optimized to address the different physicochemical properties of each extract: hydrophilic interaction liquid chromatography (HILIC) for the aqueous extract and reversed-phase chromatography for the organic. This pipeline can be generic for tissue analysis as demonstrated by applications to different tissue types. The experimental setup and fast turnaround time of the two methods contributed toward obtaining highly reproducible features with exceptional chromatographic performance (CV % < 0.5%), making this pipeline suitable for metabolic profiling applications. We structurally assigned 226 metabolites from a range of chemical classes (e.g., carnitines, α-amino acids, purines, pyrimidines, phospholipids, sphingolipids, free fatty acids, and glycerolipids) which were mapped to their corresponding pathways, biological functions and known disease mechanisms. The combination of the two untargeted UPLC-MS methods showed high metabolite complementarity. We demonstrate the application of this pipeline to cardiovascular disease, where we show that the analyzed diseased groups (n = 120) of arterial tissue could be distinguished based on their metabolic profiles. PMID:25664760

Effect of acute dietary standardization on the urinary, plasma, and salivary metabolomic profiles of healthy humans.

PubMed

Walsh, Marianne C; Brennan, Lorraine; Malthouse, J Paul G; Roche, Helen M; Gibney, Michael J

2006-09-01

Metabolomics in human nutrition research is faced with the challenge that changes in metabolic profiles resulting from diet may be difficult to differentiate from normal physiologic variation. We assessed the extent of intra- and interindividual variation in normal human metabolic profiles and investigated the effect of standardizing diet on reducing variation. Urine, plasma, and saliva were collected from 30 healthy volunteers (23 females, 7 males) on 4 separate mornings. For visits 1 and 2, free food choice was permitted on the day before biofluid collection. Food choice on the day before visit 3 was intended to mimic that for visit 2, and all foods were standardized on the day before visit 4. Samples were analyzed by using 1H nuclear magnetic resonance spectroscopy followed by multivariate data analysis. Intra- and interindividual variations were considerable for each biofluid. Visual inspection of the principal components analysis scores plots indicated a reduction in interindividual variation in urine, but not in plasma or saliva, after the standard diet. Partial least-squares discriminant analysis indicated time-dependent changes in urinary and salivary samples, mainly resulting from creatinine in urine and acetate in saliva. The predictive power of each model to classify the samples as either night or morning was 85% for urine and 75% for saliva. Urine represented a sensitive metabolic profile that reflected acute dietary intake, whereas plasma and saliva did not. Future metabolomics studies should consider recent dietary intake and time of sample collection as a means of reducing normal physiologic variation.

Intervention Trials with the Mediterranean Diet in Cardiovascular Prevention: Understanding Potential Mechanisms through Metabolomic Profiling.

PubMed

Martínez-González, Miguel Á; Ruiz-Canela, Miguel; Hruby, Adela; Liang, Liming; Trichopoulou, Antonia; Hu, Frank B

2016-03-09

Large observational epidemiologic studies and randomized trials support the benefits of a Mediterranean dietary pattern on cardiovascular disease (CVD). Mechanisms postulated to mediate these benefits include the reduction of low-grade inflammation, increased adiponectin concentrations, decreased blood coagulation, enhanced endothelial function, lower oxidative stress, lower concentrations of oxidized LDL, and improved apolipoprotein profiles. However, the metabolic pathways through which the Mediterranean diet influences CVD risk remain largely unknown. Investigating specific mechanisms in the context of a large intervention trial with the use of high-throughput metabolomic profiling will provide more solid public health messages and may help to identify key molecular targets for more effective prevention and management of CVD. Although metabolomics is not without its limitations, the techniques allow for an assessment of thousands of metabolites, providing wide-ranging profiling of small molecules related to biological status. Specific candidate plasma metabolites that may be associated with CVD include branched-chain and aromatic amino acids; the glutamine-to-glutamate ratio; some short- to medium-chain acylcarnitines; gut flora metabolites (choline, betaine, and trimethylamine N-oxide); urea cycle metabolites (citrulline and ornithine); and specific lipid subclasses. In addition to targeted metabolites, the role of a large number of untargeted metabolites should also be assessed. Large intervention trials with the use of food patterns for the prevention of CVD provide an unparalleled opportunity to examine the effects of these interventions on plasma concentrations of specific metabolites and determine whether such changes mediate the benefits of the dietary interventions on CVD risk. © 2016 American Society for Nutrition.

Metabolomic characterization of rhubarb species by capillary electrophoresis and ultra-high-pressure liquid chromatography.

PubMed

Tseng, Yufeng Jane; Kuo, Chun-Ting; Wang, San-Yuan; Liao, Hsiao-Wei; Chen, Guan-Yuan; Ku, Yuan-Ling; Shao, Wei-Cheng; Kuo, Ching-Hua

2013-10-01

This study developed CE and ultra-high-pressure LC (UHPLC) methods coupled with UV detectors to characterize the metabolomic profiles of different rhubarb species. The optimal CE conditions used a BGE with 15 mM sodium tetraborate, 15 mM sodium dihydrogen phosphate monohydrate, 30 mM sodium deoxycholate, and 30% ACN v/v at pH 8.3. The optimal UHPLC conditions used a mobile phase composed of 0.05% phosphate buffer and ACN with gradient elution. The gradient profile increased linearly from 10 to 21% ACN within the first 25 min, then increased to 33% ACN for the next 10 min. It took another 5 min to reach the 65% ACN, then for the next 5 min, it stayed unchanged. Sixteen samples of Rheum officinale and Rheum tanguticum collected from various locations were analyzed by CE and UHPLC methods. The metabolite profiles of CE were aligned and baseline corrected before chemometric analysis. Metabolomic signatures of rhubarb species from CE and UHPLC were clustered using principle component analysis and distance-based redundancy analysis; the clusters were not only able to discriminate different species but also different cultivation regions. Similarity measurements were performed by calculating the correlation coefficient of each sample with the authentic samples. Hybrid rhizome was clearly identified through similarity measurement of UHPLC metabolite profile and later confirmed by gene sequencing. The present study demonstrated that CE and UHPLC are efficient and effective tools to identify and authenticate herbs even coupled with simple detectors. © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Key metabolites in tissue extracts of Elliptio complanata identified using 1H nuclear magnetic resonance spectroscopy

PubMed Central

Hurley-Sanders, Jennifer L.; Levine, Jay F.; Nelson, Stacy A. C.; Law, J. M.; Showers, William J.; Stoskopf, Michael K.

2015-01-01

We used 1H nuclear magnetic resonance spectroscopy to describe key metabolites of the polar metabolome of the freshwater mussel, Elliptio complanata. Principal components analysis documented variability across tissue types and river of origin in mussels collected from two rivers in North Carolina (USA). Muscle, digestive gland, mantle and gill tissues yielded identifiable but overlapping metabolic profiles. Variation in digestive gland metabolic profiles between the two mussel collection sites was characterized by differences in mono- and disaccharides. Variation in mantle tissue metabolomes appeared to be associated with sex. Nuclear magnetic resonance spectroscopy is a sensitive means to detect metabolites in the tissues of E. complanata and holds promise as a tool for the investigation of freshwater mussel health and physiology. PMID:27293708

Phenotypic mapping of metabolic profiles using self-organizing maps of high-dimensional mass spectrometry data.

PubMed

Goodwin, Cody R; Sherrod, Stacy D; Marasco, Christina C; Bachmann, Brian O; Schramm-Sapyta, Nicole; Wikswo, John P; McLean, John A

2014-07-01

A metabolic system is composed of inherently interconnected metabolic precursors, intermediates, and products. The analysis of untargeted metabolomics data has conventionally been performed through the use of comparative statistics or multivariate statistical analysis-based approaches; however, each falls short in representing the related nature of metabolic perturbations. Herein, we describe a complementary method for the analysis of large metabolite inventories using a data-driven approach based upon a self-organizing map algorithm. This workflow allows for the unsupervised clustering, and subsequent prioritization of, correlated features through Gestalt comparisons of metabolic heat maps. We describe this methodology in detail, including a comparison to conventional metabolomics approaches, and demonstrate the application of this method to the analysis of the metabolic repercussions of prolonged cocaine exposure in rat sera profiles.

Chemical profiling of two congeneric sea mat corals along the Brazilian coast: adaptive and functional patterns.

PubMed

Costa-Lotufo, L V; Carnevale-Neto, F; Trindade-Silva, A E; Silva, R R; Silva, G G Z; Wilke, D V; Pinto, F C L; Sahm, B D B; Jimenez, P C; Mendonça, J N; Lotufo, T M C; Pessoa, O D L; Lopes, N P

2018-02-20

Metabolomic profiles were explored to understand environmental and taxonomic influences on the metabolism of two congeneric zoanthids, Palythoa caribaeorum and P. variabilis, collected across distinct geographical ranges. Integrated mass spectrometry data suggested the major influence of geographical location on chemical divergence when compared to species differentiation.

Global metabolic profiling procedures for urine using UPLC-MS.

PubMed

Want, Elizabeth J; Wilson, Ian D; Gika, Helen; Theodoridis, Georgios; Plumb, Robert S; Shockcor, John; Holmes, Elaine; Nicholson, Jeremy K

2010-06-01

The production of 'global' metabolite profiles involves measuring low molecular-weight metabolites (<1 kDa) in complex biofluids/tissues to study perturbations in response to physiological challenges, toxic insults or disease processes. Information-rich analytical platforms, such as mass spectrometry (MS), are needed. Here we describe the application of ultra-performance liquid chromatography-MS (UPLC-MS) to urinary metabolite profiling, including sample preparation, stability/storage and the selection of chromatographic conditions that balance metabolome coverage, chromatographic resolution and throughput. We discuss quality control and metabolite identification, as well as provide details of multivariate data analysis approaches for analyzing such MS data. Using this protocol, the analysis of a sample set in 96-well plate format, would take ca. 30 h, including 1 h for system setup, 1-2 h for sample preparation, 24 h for UPLC-MS analysis and 1-2 h for initial data processing. The use of UPLC-MS for metabolic profiling in this way is not faster than the conventional HPLC-based methods but, because of improved chromatographic performance, provides superior metabolome coverage.

Metabolomic signature of brain cancer.

PubMed

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

2017-11-01

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

Emerging field of metabolomics: big promise for cancer biomarker identification and drug discovery.

PubMed

Patel, Seema; Ahmed, Shadab

2015-03-25

Most cancers are lethal and metabolic alterations are considered a hallmark of this deadly disease. Genomics and proteomics have contributed vastly to understand cancer biology. Still there are missing links as downstream to them molecular divergence occurs. Metabolomics, the omic science that furnishes a dynamic portrait of metabolic profile is expected to bridge these gaps and boost cancer research. Metabolites being the end products are more stable than mRNAs or proteins. Previous studies have shown the efficacy of metabolomics in identifying biomarkers associated with diagnosis, prognosis and treatment of cancer. Metabolites are highly informative about the functional status of the biological system, owing to their proximity to organismal phenotypes. Scores of publications have reported about high-throughput data generation by cutting-edge analytic platforms (mass spectrometry and nuclear magnetic resonance). Further sophisticated statistical softwares (chemometrics) have enabled meaningful information extraction from the metabolomic data. Metabolomics studies have demonstrated the perturbation in glycolysis, tricarboxylic acid cycle, choline and fatty acid metabolism as traits of cancer cells. This review discusses the latest progress in this field, the future trends and the deficiencies to be surmounted for optimally implementation in oncology. The authors scoured through the most recent, high-impact papers archived in Pubmed, ScienceDirect, Wiley and Springer databases to compile this review to pique the interest of researchers towards cancer metabolomics. Copyright © 2014 Elsevier B.V. All rights reserved.

Gut metabolome meets microbiome: A methodological perspective to understand the relationship between host and microbe.

PubMed

Lamichhane, Santosh; Sen, Partho; Dickens, Alex M; Orešič, Matej; Bertram, Hanne Christine

2018-04-30

It is well established that gut microbes and their metabolic products regulate host metabolism. The interactions between the host and its gut microbiota are highly dynamic and complex. In this review we present and discuss the metabolomic strategies to study the gut microbial ecosystem. We highlight the metabolic profiling approaches to study faecal samples aimed at deciphering the metabolic product derived from gut microbiota. We also discuss how metabolomics data can be integrated with metagenomics data derived from gut microbiota and how such approaches may lead to better understanding of the microbial functions. Finally, the emerging approaches of genome-scale metabolic modelling to study microbial co-metabolism and host-microbe interactions are highlighted. Copyright © 2018 Elsevier Inc. All rights reserved.

Robust automated mass spectra interpretation and chemical formula calculation using mixed integer linear programming.

PubMed

Baran, Richard; Northen, Trent R

2013-10-15

Untargeted metabolite profiling using liquid chromatography and mass spectrometry coupled via electrospray ionization is a powerful tool for the discovery of novel natural products, metabolic capabilities, and biomarkers. However, the elucidation of the identities of uncharacterized metabolites from spectral features remains challenging. A critical step in the metabolite identification workflow is the assignment of redundant spectral features (adducts, fragments, multimers) and calculation of the underlying chemical formula. Inspection of the data by experts using computational tools solving partial problems (e.g., chemical formula calculation for individual ions) can be performed to disambiguate alternative solutions and provide reliable results. However, manual curation is tedious and not readily scalable or standardized. Here we describe an automated procedure for the robust automated mass spectra interpretation and chemical formula calculation using mixed integer linear programming optimization (RAMSI). Chemical rules among related ions are expressed as linear constraints and both the spectra interpretation and chemical formula calculation are performed in a single optimization step. This approach is unbiased in that it does not require predefined sets of neutral losses and positive and negative polarity spectra can be combined in a single optimization. The procedure was evaluated with 30 experimental mass spectra and was found to effectively identify the protonated or deprotonated molecule ([M + H](+) or [M - H](-)) while being robust to the presence of background ions. RAMSI provides a much-needed standardized tool for interpreting ions for subsequent identification in untargeted metabolomics workflows.

Functional metabolomics as a tool to analyze Mediator function and structure in plants.

PubMed

Davoine, Celine; Abreu, Ilka N; Khajeh, Khalil; Blomberg, Jeanette; Kidd, Brendan N; Kazan, Kemal; Schenk, Peer M; Gerber, Lorenz; Nilsson, Ove; Moritz, Thomas; Björklund, Stefan

2017-01-01

Mediator is a multiprotein transcriptional co-regulator complex composed of four modules; Head, Middle, Tail, and Kinase. It conveys signals from promoter-bound transcriptional regulators to RNA polymerase II and thus plays an essential role in eukaryotic gene regulation. We describe subunit localization and activities of Mediator in Arabidopsis through metabolome and transcriptome analyses from a set of Mediator mutants. Functional metabolomic analysis based on the metabolite profiles of Mediator mutants using multivariate statistical analysis and heat-map visualization shows that different subunit mutants display distinct metabolite profiles, which cluster according to the reported localization of the corresponding subunits in yeast. Based on these results, we suggest localization of previously unassigned plant Mediator subunits to specific modules. We also describe novel roles for individual subunits in development, and demonstrate changes in gene expression patterns and specific metabolite levels in med18 and med25, which can explain their phenotypes. We find that med18 displays levels of phytoalexins normally found in wild type plants only after exposure to pathogens. Our results indicate that different Mediator subunits are involved in specific signaling pathways that control developmental processes and tolerance to pathogen infections.

Comparative study of single/combination use of Huang-Lian-Jie-Du decoction and berberine on their protection on sepsis induced acute liver injury by NMR metabolic profiling.

PubMed

Lv, Yan; Wang, Junsong; Xu, Dingqiao; Liao, Shanting; Li, Pei; Zhang, Qian; Yang, Minghua; Kong, Lingyi

2017-10-25

Sepsis is a serious clinical disease with a high mortality rate all around the world. Liver organ dysfunction is an important sign for the severity and outcome of sepsis in patients. In this study, 1 H NMR-based metabolomics approach and biochemical assays were applied to investigate the metabolic profiling for cecal ligation and puncture (CLP) induced acute liver injury, the therapeutical effect of single/combination use of Huang-Lian-Jie-Du decoction (HLJDD) and berberine, and the interaction of them. Metabolomics analysis revealed significant perturbations in livers of septic rats, which could be ameliorated by HLJDD, berberine and their combination treatment. Berberine could better rectified glycolysis and nucleic acid metabolism in the liver. HLJDD had exceptional better anti-inflammatory, antibacterial and antioxidative effects than berberine. The interaction of berberine and HLJDD could further strengthen the anti-inflammation and anti-oxidation, but with poor effect on amino acids metabolism. These findings highlighted the feasibility of the integrated NMR based metabolomics approach to understand the pathogenesis of diseases, the action mechanisms of therapy and the herb-drug interaction. Copyright © 2017 Elsevier B.V. All rights reserved.

Nontargeted metabolite profiles and sensory properties of strawberry cultivars grown both organically and conventionally.

PubMed

Kårlund, Anna; Hanhineva, Kati; Lehtonen, Marko; Karjalainen, Reijo O; Sandell, Mari

2015-01-28

Strawberry (Fragaria × ananassa Duch.) contains many secondary metabolites potentially beneficial for human health, and several of these compounds contribute to strawberry sensory properties, as well. In this study, three strawberry cultivars grown both conventionally and organically were subjected to nontargeted metabolite profiling analysis with LC-qTOF-ESI-MS and to descriptive sensory evaluation by a trained panel. Combined metabolome and sensory data (PLS model) revealed that 79% variation in the metabolome explained 88% variation in the sensory profiles. Flavonoids and condensed and hydrolyzable tannins determined the orosensory properties, and fatty acids contributed to the odor attributes of strawberry. Overall, the results indicated that the chemical composition and sensory quality of strawberries grown in different cultivation systems vary mostly according to cultivar. Organic farming practices may enhance the accumulation of some plant metabolites in specific strawberry genotypes. Careful cultivar selection is a key factor for the improvement of nutritional quality and marketing value of organic strawberries.

(1)H NMR metabolomic profiling of the blue crab (Callinectes sapidus) from the Adriatic Sea (SE Italy): A comparison with warty crab (Eriphia verrucosa), and edible crab (Cancer pagurus).

PubMed

Zotti, Maurizio; De Pascali, Sandra Angelica; Del Coco, Laura; Migoni, Danilo; Carrozzo, Leonardo; Mancinelli, Giorgio; Fanizzi, Francesco Paolo

2016-04-01

The metabolomic profile of blue crab (Callinectes sapidus) captured in the Acquatina lagoon (SE Italy) was compared to an autochthonous (Eriphia verrucosa) and to a commercial crab species (Cancer pagurus). Both lipid and aqueous extracts of raw claw muscle were analyzed by (1)H NMR spectroscopy and MVA (multivariate data analysis). Aqueous extracts were characterized by a higher inter-specific discriminating power compared to lipid fractions. Specifically, higher levels of glutamate, alanine and glycine characterized the aqueous extract of C. sapidus, while homarine, lactate, betaine and taurine characterized E. verrucosa and C. pagurus. On the other hand, only the signals of monounsaturated fatty acids distinguished the lipid profiles of the three crab species. These results support the commercial exploitation and the integration of the blue crab in human diet of European countries as an healthy and valuable seafood. Copyright © 2015 Elsevier Ltd. All rights reserved.

Metabolic profiling reveals that time related physiological changes in mammalian cell perfusion cultures are bioreactor scale independent.

PubMed

Vernardis, Spyros I; Goudar, Chetan T; Klapa, Maria I

2013-09-01

Metabolic profiling was used to characterize the time course of cell physiology both in laboratory- and manufacturing-scale mammalian cell perfusion cultures. Two independent experiments were performed involving three vials from the same BHK cell bank, used to inoculate three laboratory-scale bioreactors, from which four manufacturing-scale cultures were initiated. It was shown that metabolomic analysis can indeed enhance the prime variable dataset for the monitoring of perfusion cultures by providing a higher resolution view of the metabolic state. Metabolic profiles could capture physiological state shifts over the course of the perfusion cultures and indicated a metabolic "signature" of the phase transitions, which was not observable from prime variable data. Specifically, the vast majority of metabolites had lower concentrations in the middle compared to the other two phases. Notably, metabolomics provided orthogonal (to prime variables) evidence that all cultures followed this same metabolic state shift with cell age, independently of bioreactor scale. © 2013 Elsevier Inc. All rights reserved.

Raman-based noninvasive metabolic profile evaluation of in vitro bovine embryos

NASA Astrophysics Data System (ADS)

dos Santos, Érika Cristina; Martinho, Herculano; Annes, Kelly; da Silva, Thais; Soares, Carlos Alexandre; Leite, Roberta Ferreira; Milazzotto, Marcella Pecora

2016-07-01

The timing of the first embryonic cell divisions may predict the ability of an embryo to establish pregnancy. Similarly, metabolic profiles may be markers of embryonic viability. However, in bovine, data about the metabolomics profile of these embryos are still not available. In the present work, we describe Raman-based metabolomic profiles of culture media of bovine embryos with different developmental kinetics (fast x slow) throughout the in vitro culture. The principal component analysis enabled us to classify embryos with different developmental kinetics since they presented specific spectroscopic profiles for each evaluated time point. We noticed that bands at 1076 cm-1 (lipids), 1300 cm-1 (Amide III), and 2719 cm-1 (DNA nitrogen bases) gave the most relevant spectral features, enabling the separation between fast and slow groups. Bands at 1001 cm-1 (phenylalanine) and 2892 cm-1 (methylene group of the polymethylene chain) presented specific patterns related to embryonic stage and can be considered as biomarkers of embryonic development by Raman spectroscopy. The culture media analysis by Raman spectroscopy proved to be a simple and sensitive technique that can be applied with high efficiency to characterize the profiles of in vitro produced bovine embryos with different development kinetics and different stages of development.

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

NASA Astrophysics Data System (ADS)

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 low application doses; (vi) regarding plant metabolomics study, all treatments showed a different metabolites in respect to Ctrl- treatment. BSG, LPR and Ctrl+ treatments had similar metabolic profile. Finally, Metabolomic study provided an efficient tool and a key reporter about bio-effectors impact on plants. The visible effect and measured agronomical parameters was emphasized and demonstrated by metabolic profiling which offer insights into the affected plant metabolic pathways. As conclusion, our results supported the prediction that plant derived materials may interfere again in plant production regardless their nutritional content. Keywords: Bio-effectors; Metabolomics; Nuclear Magnetic Resonance (NMR); Barley; Fennel; Lemon; Tomato.

Metabolomic signatures distinguish the impact of formula carbohydrates on disease outcome in a preterm piglet model of NEC.

PubMed

Call, Lee; Stoll, Barbara; Oosterloo, Berthe; Ajami, Nadim; Sheikh, Fariha; Wittke, Anja; Waworuntu, Rosaline; Berg, Brian; Petrosino, Joseph; Olutoye, Oluyinka; Burrin, Douglas

2018-06-19

Major risk factors for necrotizing enterocolitis (NEC) include premature birth and formula feeding in the context of microbial colonization of the gastrointestinal tract. We previously showed that feeding formula composed of lactose vs. corn syrup solids protects against NEC in preterm pigs; however, the microbial and metabolic effects of these different carbohydrates used in infant formula has not been explored. Our objective was to characterize the effects of lactose- and corn syrup solid-based formulas on the metabolic and microbial profiles of preterm piglets and to determine whether unique metabolomic or microbiome signatures correlate with severity or incidence of NEC. Preterm piglets (103 days gestation) were given total parenteral nutrition (2 days) followed by gradual (5 days) advancement of enteral feeding of formulas matched in nutrient content but containing either lactose (LAC), corn syrup solids (CSS), or 1:1 mix (MIX). Gut contents and mucosal samples were collected and analyzed for microbial profiles by sequencing the V4 region of the 16S rRNA gene. Metabolomic profiles of cecal contents and plasma were analyzed by LC/GC mass spectrometry. NEC incidence was 14, 50, and 44% in the LAC, MIX, and CSS groups, respectively. The dominant classes of bacteria were Bacilli, Clostridia, and Gammaproteobacteria. The number of observed OTUs was lowest in colon contents of CSS-fed pigs. CSS-based formula was associated with higher Bacilli and lower Clostridium from clusters XIVa and XI in the colon. NEC was associated with decreased Gammaproteobacteria in the stomach and increased Clostridium sensu stricto in the ileum. Plasma from NEC piglets was enriched with metabolites of purine metabolism, aromatic amino acid metabolism, and bile acids. Markers of glycolysis, e.g., lactate, were increased in the cecal contents of CSS-fed pigs and in plasma of pigs which developed NEC. Feeding formula containing lactose is not completely protective against NEC, yet selects for greater microbial richness associated with changes in Bacilli and Clostridium and lower NEC incidence. We conclude that feeding preterm piglets a corn syrup solid vs. lactose-based formula increases the incidence of NEC and produces distinct metabolomic signatures despite modest changes in microbiome profiles.

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

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

Rivas-Ubach, Albert; Barbeta, Adrià; Sardans, Jordi

Soils provide physical support, water, and nutrients to terrestrial plants. Upper soil layers are crucial for forest dynamics, especially under drought conditions, because many biological processes occur there and provide support, water and nutrients to terrestrial plants. We postulated that tree size and overall plant function manifested in the metabolome composition, the total set of metabolites, were dependent on the depth of upper soil layers and on water availability. We sampled leaves for stoichiometric and metabolomic analyses once per season from differently sized Quercus ilex trees under natural and experimental drought conditions as projected for the coming decades. Different sizedmore » trees had different metabolomes and plots with shallower soils had smaller trees. Soil moisture of the upper soil did not explain the tree size and smaller trees did not show higher concentrations of biomarker metabolites related to drought stress. However, the impact of drought treatment on metabolomes was higher in smaller trees in shallower soils. Our results suggested that tree size was more dependent on the depth of the upper soil layers, which indirectly affect the metabolomes of the trees, than on the moisture content of the upper soil layers. Metabolomic profiling of Q. ilex supported the premise that water availability in the upper soil layers was not necessarily correlated with tree size. The higher impact of drought on trees growing in shallower soils nevertheless indicates a higher vulnerability of small trees to the future increase in frequency, intensity, and duration of drought projected for the Mediterranean Basin and other areas. Metabolomics has proven to be an excellent tool detecting significant metabolic changes among differently sized individuals of the same species and it improves our understanding of the connection between plant metabolomes and environmental variables such as soil depth and moisture content.« less

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

PubMed Central

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

2015-01-01

Dietary restriction (DR) is a robust intervention that extends lifespan and slows the onset of age-related diseases in diverse organisms. While significant progress has been made in attempts to uncover the genetic mechanisms of DR, there are few studies on the effects of DR on the metabolome. In recent years, metabolomic profiling has emerged as a powerful technology to understand the molecular causes and consequences of natural aging and disease-associated phenotypes. Here, we use high-resolution mass spectroscopy and novel computational approaches to examine changes in the metabolome from the head, thorax, abdomen, and whole body at multiple ages in Drosophila fed either a nutrient-rich ad libitum (AL) or nutrient-restricted (DR) diet. Multivariate analysis clearly separates the metabolome by diet in different tissues and different ages. DR significantly altered the metabolome and, in particular, slowed age-related changes in the metabolome. Interestingly, we observed interacting metabolites whose correlation coefficients, but not mean levels, differed significantly between AL and DR. The number and magnitude of positively correlated metabolites was greater under a DR diet. Furthermore, there was a decrease in positive metabolite correlations as flies aged on an AL diet. Conversely, DR enhanced these correlations with age. Metabolic set enrichment analysis identified several known (e.g., amino acid and NAD metabolism) and novel metabolic pathways that may affect how DR effects aging. Our results suggest that network structure of metabolites is altered upon DR and may play an important role in preventing the decline of homeostasis with age. PMID:26085309

Shifts in plant foliar and floral metabolomes in response to the suppression of the associated microbiota.

PubMed

Gargallo-Garriga, Albert; Sardans, Jordi; Pérez-Trujillo, Míriam; Guenther, Alex; Llusià, Joan; Rico, Laura; Terradas, Jaume; Farré-Armengol, Gerard; Filella, Iolanda; Parella, Teodor; Peñuelas, Josep

2016-04-06

The phyllospheric microbiota is assumed to play a key role in the metabolism of host plants. Its role in determining the epiphytic and internal plant metabolome, however, remains to be investigated. We analyzed the Liquid Chromatography-Mass Spectrometry (LC-MS) profiles of the epiphytic and internal metabolomes of the leaves and flowers of Sambucus nigra with and without external antibiotic treatment application. The epiphytic metabolism showed a degree of complexity similar to that of the plant organs. The suppression of microbial communities by topical applications of antibiotics had a greater impact on the epiphytic metabolome than on the internal metabolomes of the plant organs, although even the latter changed significantly both in leaves and flowers. The application of antibiotics decreased the concentration of lactate in both epiphytic and organ metabolomes, and the concentrations of citraconic acid, acetyl-CoA, isoleucine, and several secondary compounds such as terpenes and phenols in the epiphytic extracts. The metabolite pyrogallol appeared in the floral epiphytic community only after the treatment. The concentrations of the amino acid precursors of the ketoglutarate-synthesis pathway tended to decrease in the leaves and to increase in the foliar epiphytic extracts. These results suggest that anaerobic and/or facultative anaerobic bacteria were present in high numbers in the phyllosphere and in the apoplasts of S. nigra. The results also show that microbial communities play a significant role in the metabolomes of plant organs and could have more complex and frequent mutualistic, saprophytic, and/or parasitic relationships with internal plant metabolism than currently assumed.

Analysis of Human Plasma Metabolites across Different Liquid Chromatography - Mass Spectrometry Platforms: Cross-platform Transferable Chemical Signatures

PubMed Central

Telu, Kelly H.; Yan, Xinjian; Wallace, William E.; Stein, Stephen E.; Simón-Manso, Yamil

2016-01-01

RATIONALE The metabolite profiling of a NIST plasma Standard Reference Material (SRM 1950) on different LC-MS platforms showed significant differences. Although these findings suggest caution when interpreting metabolomics results, the degree of overlap of both profiles allowed us to use tandem mass spectral libraries of recurrent spectra to evaluate to what extent these results are transferable across platforms and to develop cross-platform chemical signatures. METHODS Non-targeted global metabolite profiles of SRM 1950 were obtained on different LC-MS platforms using reversed phase chromatography and different chromatographic scales (nano, conventional and UHPLC). The data processing and the metabolite differential analysis were carried out using publically available (XCMS), proprietary (Mass Profiler Professional) and in-house software (NIST pipeline). RESULTS Repeatability and intermediate precision showed that the non-targeted SRM 1950 profiling was highly reproducible when working on the same platform (RSD < 2%); however, substantial differences were found in the LC-MS patterns originating on different platforms or even using different chromatographic scales (conventional HPLC, UHPLC and nanoLC) on the same platform. A substantial degree of overlap (common molecular features) was also found. A procedure to generate consistent chemical signatures using tandem mass spectral libraries of recurrent spectra is proposed. CONLUSIONS Different platforms rendered significantly different metabolite profiles, but the results were highly reproducible when working within one platform. Tandem mass spectral libraries of recurrent spectra are proposed to evaluate the degree of transferability of chemical signatures generated on different platforms. Chemical signatures based on our procedure are most likely cross-platform transferable. PMID:26842580

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

PubMed

Zhao, Shuang; Luo, Xian; Li, Liang

2016-11-01

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

CEBS object model for systems biology data, SysBio-OM.

PubMed

Xirasagar, Sandhya; Gustafson, Scott; Merrick, B Alex; Tomer, Kenneth B; Stasiewicz, Stanley; Chan, Denny D; Yost, Kenneth J; Yates, John R; Sumner, Susan; Xiao, Nianqing; Waters, Michael D

2004-09-01

To promote a systems biology approach to understanding the biological effects of environmental stressors, the Chemical Effects in Biological Systems (CEBS) knowledge base is being developed to house data from multiple complex data streams in a systems friendly manner that will accommodate extensive querying from users. Unified data representation via a single object model will greatly aid in integrating data storage and management, and facilitate reuse of software to analyze and display data resulting from diverse differential expression or differential profile technologies. Data streams include, but are not limited to, gene expression analysis (transcriptomics), protein expression and protein-protein interaction analysis (proteomics) and changes in low molecular weight metabolite levels (metabolomics). To enable the integration of microarray gene expression, proteomics and metabolomics data in the CEBS system, we designed an object model, Systems Biology Object Model (SysBio-OM). The model is comprehensive and leverages other open source efforts, namely the MicroArray Gene Expression Object Model (MAGE-OM) and the Proteomics Experiment Data Repository (PEDRo) object model. SysBio-OM is designed by extending MAGE-OM to represent protein expression data elements (including those from PEDRo), protein-protein interaction and metabolomics data. SysBio-OM promotes the standardization of data representation and data quality by facilitating the capture of the minimum annotation required for an experiment. Such standardization refines the accuracy of data mining and interpretation. The open source SysBio-OM model, which can be implemented on varied computing platforms is presented here. A universal modeling language depiction of the entire SysBio-OM is available at http://cebs.niehs.nih.gov/SysBioOM/. The Rational Rose object model package is distributed under an open source license that permits unrestricted academic and commercial use and is available at http://cebs.niehs.nih.gov/cebsdownloads. The database and interface are being built to implement the model and will be available for public use at http://cebs.niehs.nih.gov.

Gaussian graphical modeling reconstructs pathway reactions from high-throughput metabolomics data

PubMed Central

2011-01-01

Background With the advent of high-throughput targeted metabolic profiling techniques, the question of how to interpret and analyze the resulting vast amount of data becomes more and more important. In this work we address the reconstruction of metabolic reactions from cross-sectional metabolomics data, that is without the requirement for time-resolved measurements or specific system perturbations. Previous studies in this area mainly focused on Pearson correlation coefficients, which however are generally incapable of distinguishing between direct and indirect metabolic interactions. Results In our new approach we propose the application of a Gaussian graphical model (GGM), an undirected probabilistic graphical model estimating the conditional dependence between variables. GGMs are based on partial correlation coefficients, that is pairwise Pearson correlation coefficients conditioned against the correlation with all other metabolites. We first demonstrate the general validity of the method and its advantages over regular correlation networks with computer-simulated reaction systems. Then we estimate a GGM on data from a large human population cohort, covering 1020 fasting blood serum samples with 151 quantified metabolites. The GGM is much sparser than the correlation network, shows a modular structure with respect to metabolite classes, and is stable to the choice of samples in the data set. On the example of human fatty acid metabolism, we demonstrate for the first time that high partial correlation coefficients generally correspond to known metabolic reactions. This feature is evaluated both manually by investigating specific pairs of high-scoring metabolites, and then systematically on a literature-curated model of fatty acid synthesis and degradation. Our method detects many known reactions along with possibly novel pathway interactions, representing candidates for further experimental examination. Conclusions In summary, we demonstrate strong signatures of intracellular pathways in blood serum data, and provide a valuable tool for the unbiased reconstruction of metabolic reactions from large-scale metabolomics data sets. PMID:21281499

Biomarkers of Coordinate Metabolic Reprogramming in Colorectal Tumors in Mice and Humans

PubMed Central

Manna, Soumen K.; Tanaka, Naoki; Krausz, Kristopher W.; Haznadar, Majda; Xue, Xiang; Matsubara, Tsutomu; Bowman, Elise D.; Fearon, Eric R.; Harris, Curtis C.; Shah, Yatrik M.; Gonzalez, Frank J.

2014-01-01

BACKGROUND & AIMS There are no robust noninvasive methods for colorectal cancer screening and diagnosis. Metabolomic and gene expression analyses of urine and tissue samples from mice and humans were used to identify markers of colorectal carcinogenesis. METHODS Mass spectrometry-based metabolomic analyses of urine and tissues from wild-type C57BL/6J and ApcMin/+ mice, as well as from mice with azoxymethane-induced tumors, was employed in tandem with gene expression analysis. Metabolomics profiles were also determined on colon tumor and adjacent non-tumor tissues from 39 patients. The effects of β-catenin activity on metabolic profiles were assessed in mice with colon-specific disruption of Apc. RESULTS Thirteen markers were found in urine associated with development of colorectal tumors in ApcMin/+ mice. Metabolites related to polyamine metabolism, nucleic acid metabolism, and methylation, identified tumor-bearing mice with 100% accuracy, and also accurately identified mice with polyps. Changes in gene expression in tumor samples from mice reflected the observed changes in metabolic products detected in urine; similar changes were observed in mice with azoxymethane-induced tumors and mice with colon-specific activation of β-catenin. The metabolic alterations indicated by markers in urine therefore appear to occur during early stages of tumorigenesis, when cancer cells are proliferating. In tissues from patients, tumors had stage-dependent increases in 12 metabolites associated with the same metabolic pathways identified in mice (including amino acid metabolism and polyamine metabolism). Ten metabolites that were increased in tumor tissues, compared with non-tumor tissues (proline, threonine, glutamic acid, arginine, N1-acetylspermidine, xanthine, uracil, betaine, symmetric dimethylarginine, and asymmetric-dimethylarginine), were also increased in urine from tumor-bearing mice. CONCLUSIONS Gene expression and metabolomic profiles of urine and tissue samples from mice with colorectal tumors and of colorectal tumor samples from patients revealed metabolites associated with specific metabolic changes that are indicative of early-stage tumor development. These urine and tissue markers might be used in early detection of colorectal cancer. PMID:24440673

Linking gene regulation and the exo-metabolome: A comparative transcriptomics approach to identify genes that impact on the production of volatile aroma compounds in yeast

PubMed Central

Rossouw, Debra; Næs, Tormod; Bauer, Florian F

2008-01-01

Background 'Omics' tools provide novel opportunities for system-wide analysis of complex cellular functions. Secondary metabolism is an example of a complex network of biochemical pathways, which, although well mapped from a biochemical point of view, is not well understood with regards to its physiological roles and genetic and biochemical regulation. Many of the metabolites produced by this network such as higher alcohols and esters are significant aroma impact compounds in fermentation products, and different yeast strains are known to produce highly divergent aroma profiles. Here, we investigated whether we can predict the impact of specific genes of known or unknown function on this metabolic network by combining whole transcriptome and partial exo-metabolome analysis. Results For this purpose, the gene expression levels of five different industrial wine yeast strains that produce divergent aroma profiles were established at three different time points of alcoholic fermentation in synthetic wine must. A matrix of gene expression data was generated and integrated with the concentrations of volatile aroma compounds measured at the same time points. This relatively unbiased approach to the study of volatile aroma compounds enabled us to identify candidate genes for aroma profile modification. Five of these genes, namely YMR210W, BAT1, AAD10, AAD14 and ACS1 were selected for overexpression in commercial wine yeast, VIN13. Analysis of the data show a statistically significant correlation between the changes in the exo-metabome of the overexpressing strains and the changes that were predicted based on the unbiased alignment of transcriptomic and exo-metabolomic data. Conclusion The data suggest that a comparative transcriptomics and metabolomics approach can be used to identify the metabolic impacts of the expression of individual genes in complex systems, and the amenability of transcriptomic data to direct applications of biotechnological relevance. PMID:18990252

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

PubMed

Mung, Dorothea; Li, Liang

2018-02-25

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

Metabolomic Analysis of Alfalfa (Medicago sativa L.) Root-Symbiotic Rhizobia Responses under Alkali Stress.

PubMed

Song, Tingting; Xu, Huihui; Sun, Na; Jiang, Liu; Tian, Pu; Yong, Yueyuan; Yang, Weiwei; Cai, Hua; Cui, Guowen

2017-01-01

Alkaline salts (e.g., NaHCO 3 and Na 2 CO 3 ) causes more severe morphological and physiological damage to plants than neutral salts (e.g., NaCl and Na 2 SO 4 ) due to differences in pH. The mechanism by which plants respond to alkali stress is not fully understood, especially in plants having symbotic relationships such as alfalfa ( Medicago sativa L.). Therefore, a study was designed to evaluate the metabolic response of the root-nodule symbiosis in alfalfa under alkali stress using comparative metabolomics. Rhizobium-nodulized (RI group) and non-nodulized (NI group) alfalfa roots were treated with 200 mmol/L NaHCO 3 and, roots samples were analyzed for malondialdehydyde (MDA), proline, glutathione (GSH), superoxide dismutase (SOD), and peroxidase (POD) content. Additionally, metabolite profiling was conducted using gas chromatography combined with time-of-flight mass spectrometry (GC/TOF-MS). Phenotypically, the RI alfalfa exhibited a greater resistance to alkali stress than the NI plants examined. Physiological analysis and metabolic profiling revealed that RI plants accumulated more antioxidants (SOD, POD, GSH), osmolytes (sugar, glycols, proline), organic acids (succinic acid, fumaric acid, and alpha-ketoglutaric acid), and metabolites that are involved in nitrogen fixation. Our pairwise metabolomics comparisons revealed that RI alfalfa plants exhibited a distinct metabolic profile associated with alkali putative tolerance relative to NI alfalfa plants. Data provide new information about the relationship between non-nodulized, rhizobium-nodulized alfalfa and alkali resistance.

Metabolomic Analysis of Alfalfa (Medicago sativa L.) Root-Symbiotic Rhizobia Responses under Alkali Stress

PubMed Central

Song, Tingting; Xu, Huihui; Sun, Na; Jiang, Liu; Tian, Pu; Yong, Yueyuan; Yang, Weiwei; Cai, Hua; Cui, Guowen

2017-01-01

Alkaline salts (e.g., NaHCO3 and Na2CO3) causes more severe morphological and physiological damage to plants than neutral salts (e.g., NaCl and Na2SO4) due to differences in pH. The mechanism by which plants respond to alkali stress is not fully understood, especially in plants having symbotic relationships such as alfalfa (Medicago sativa L.). Therefore, a study was designed to evaluate the metabolic response of the root-nodule symbiosis in alfalfa under alkali stress using comparative metabolomics. Rhizobium-nodulized (RI group) and non-nodulized (NI group) alfalfa roots were treated with 200 mmol/L NaHCO3 and, roots samples were analyzed for malondialdehydyde (MDA), proline, glutathione (GSH), superoxide dismutase (SOD), and peroxidase (POD) content. Additionally, metabolite profiling was conducted using gas chromatography combined with time-of-flight mass spectrometry (GC/TOF-MS). Phenotypically, the RI alfalfa exhibited a greater resistance to alkali stress than the NI plants examined. Physiological analysis and metabolic profiling revealed that RI plants accumulated more antioxidants (SOD, POD, GSH), osmolytes (sugar, glycols, proline), organic acids (succinic acid, fumaric acid, and alpha-ketoglutaric acid), and metabolites that are involved in nitrogen fixation. Our pairwise metabolomics comparisons revealed that RI alfalfa plants exhibited a distinct metabolic profile associated with alkali putative tolerance relative to NI alfalfa plants. Data provide new information about the relationship between non-nodulized, rhizobium-nodulized alfalfa and alkali resistance. PMID:28744296

The differential metabolite profiles of acute lymphoblastic leukaemic patients treated with 6-mercaptopurine using untargeted metabolomics approach.

PubMed

Bannur, Z; Teh, L K; Hennesy, T; Rosli, W R W; Mohamad, N; Nasir, A; Ankathil, R; Zakaria, Z A; Baba, A; Salleh, M Z

2014-04-01

Acute lymphoblastic leukaemia (ALL) has posed challenges to the clinician due to variable patients' responses and late diagnosis. With the advance in metabolomics, early detection and personalised treatment are possible. Metabolomic profile of 21 ALL patients treated with 6-mercaptopurine and 10 healthy volunteers were analysed using liquid chromatography/mass spectrometry quadrupole-time of flight (LC/MS Q-TOF). Principal components analysis (PCA), recursive analysis, clustering and pathway analysis were performed using MassHunter Qualitative and Mass Profiler Professional (MPP) software. Several metabolites were found to be expressed differently in patients treated with 6-mercaptopurine. Interestingly, 13 metabolites were significantly differently expressed [p-value <0.01 (unpaired t-test) and 2-fold change] in 19% of the patients who had relapses in their treatment. Down-regulated metabolites in relapsed patients were 1-tetrahexanoyl-2-(8-[3]-ladderane-octanyl)-sn-GPEtn, GPEtn (18:1(9Z)/0:0), GPCho(O-6:0/O-6:0), GPCho(O-2:0/O-1:0), methyl 8-[2-(2-formyl-vinyl)-3-hydroxy-5-oxo-cyclopentyl]-octanoate and plasma free amino acids (PFAA). Characterizing the subjects according to their ITPA 94C>A genotypes reveal differential expression of metabolites. Our research contributes to identification of metabolites that could be used to monitor disease progress of patients and allow targeted therapy for ALL at different stages, especially in preventing complication of relapse. Copyright © 2014 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. All rights reserved.

Metabolomic Profiling of Soybeans (Glycine max L.) Reveals the Importance of Sugar and Nitrogen Metabolism under Drought and Heat Stress

PubMed Central

Das, Aayudh; Rushton, Paul J.; Rohila, Jai S.

2017-01-01

Soybean is an important crop that is continually threatened by abiotic stresses, especially drought and heat stress. At molecular levels, reduced yields due to drought and heat stress can be seen as a result of alterations in metabolic homeostasis of vegetative tissues. At present an incomplete understanding of abiotic stress-associated metabolism and identification of associated metabolites remains a major gap in soybean stress research. A study with a goal to profile leaf metabolites under control conditions (28/24 °C), drought [28/24 °C, 10% volumetric water content (VWC)], and heat stress (43/35 °C) was conducted in a controlled environment. Analyses of non-targeted metabolomic data showed that in response to drought and heat stress, key metabolites (carbohydrates, amino acids, lipids, cofactors, nucleotides, peptides and secondary metabolites) were differentially accumulated in soybean leaves. The metabolites for various cellular processes, such as glycolysis, the tricarboxylic acid (TCA) cycle, the pentose phosphate pathway, and starch biosynthesis, that regulate carbohydrate metabolism, amino acid metabolism, peptide metabolism, and purine and pyrimidine biosynthesis, were found to be affected by drought as well as heat stress. Computationally based regulatory networks predicted additional compounds that address the possibility of other metabolites and metabolic pathways that could also be important for soybean under drought and heat stress conditions. Metabolomic profiling demonstrated that in soybeans, keeping up with sugar and nitrogen metabolism is of prime significance, along with phytochemical metabolism under drought and heat stress conditions. PMID:28587097

Metabolomic Profiling in Individuals with a Failing Kidney Allograft.

PubMed

Bassi, Roberto; Niewczas, Monika A; Biancone, Luigi; Bussolino, Stefania; Merugumala, Sai; Tezza, Sara; D'Addio, Francesca; Ben Nasr, Moufida; Valderrama-Vasquez, Alessandro; Usuelli, Vera; De Zan, Valentina; El Essawy, Basset; Venturini, Massimo; Secchi, Antonio; De Cobelli, Francesco; Lin, Alexander; Chandraker, Anil; Fiorina, Paolo

2017-01-01

Alteration of certain metabolites may play a role in the pathophysiology of renal allograft disease. To explore metabolomic abnormalities in individuals with a failing kidney allograft, we analyzed by liquid chromatography-mass spectrometry (LC-MS/MS; for ex vivo profiling of serum and urine) and two dimensional correlated spectroscopy (2D COSY; for in vivo study of the kidney graft) 40 subjects with varying degrees of chronic allograft dysfunction stratified by tertiles of glomerular filtration rate (GFR; T1, T2, T3). Ten healthy non-allograft individuals were chosen as controls. LC-MS/MS analysis revealed a dose-response association between GFR and serum concentration of tryptophan, glutamine, dimethylarginine isomers (asymmetric [A]DMA and symmetric [S]DMA) and short-chain acylcarnitines (C4 and C12), (test for trend: T1-T3 = p<0.05; p = 0.01; p<0.001; p = 0.01; p = 0.01; p<0.05, respectively). The same association was found between GFR and urinary levels of histidine, DOPA, dopamine, carnosine, SDMA and ADMA (test for trend: T1-T3 = p<0.05; p<0.01; p = 0.001; p<0.05; p = 0.001; p<0.001; p<0.01, respectively). In vivo 2D COSY of the kidney allograft revealed significant reduction in the parenchymal content of choline, creatine, taurine and threonine (all: p<0.05) in individuals with lower GFR levels. We report an association between renal function and altered metabolomic profile in renal transplant individuals with different degrees of kidney graft function.

Metabolomic Profile of Ards by Nuclear Magnetic Resonance Spectroscopy in Patients with H1N1 Influenza Virus Pneumonia.

PubMed

Izquierdo-Garcia, Jose L; Nin, Nicolas; Jimenez-Clemente, Jorge; Horcajada, Juan P; Arenas-Miras, Maria Del Mar; Gea, Joaquim; Esteban, Andres; Ruiz-Cabello, Jesus; Lorente, Jose A

2017-12-29

The integrated analysis of changes in the metabolic profile could be critical for the discovery of biomarkers of lung injury, and also for generating new pathophysiological hypotheses and designing novel therapeutic targets for the acute respiratory distress syndrome (ARDS). This study aimed at developing a Nuclear Magnetic Resonance (NMR)-based approach for the identification of the metabolomic profile of ARDS in patients with H1N1 influenza virus pneumonia. Serum samples from 30 patients (derivation set) diagnosed of H1N1 influenza virus pneumonia were analysed by unsupervised Principal Component Analysis (PCA) to identify metabolic differences between patients with and without ARDS by NMR-spectroscopy. A predictive model of partial least squares discriminant analysis (PLS-DA) was developed for the identification of ARDS. PLS-DA was trained with the derivation set and tested in another set of samples from 26 patients also diagnosed of H1N1 influenza virus pneumonia (validation set). Decreased serum glucose, alanine, glutamine, methylhistidine and fatty acids concentrations, and elevated serum phenylalanine and methylguanidine concentrations, discriminated patients with ARDS versus patients without ARDS. PLS-DA model successfully identified the presence of ARDS in the validation set with a success rate of 92% (sensitivity 100% and specificity 91%). The classification functions showed a good correlation with the Sequential Organ Failure Assessment (SOFA) score (R = 0.74, p < 0.0001) and the Pa02/Fi02 ratio (R = 0.41, p = 0.03). The serum metabolomic profile is sensitive and specific to identify ARDS in patients with H1N1 influenza A pneumonia. Future studies are needed to determine the role of NMR-spectroscopy as a biomarker of ARDS.

Metabolomics and Personalized Medicine.

PubMed

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

2016-01-01

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

Metabolomic Responses of Guard Cells and Mesophyll Cells to Bicarbonate

PubMed Central

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

2015-01-01

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

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

PubMed Central

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

2014-01-01

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

Water-soluble vitamin homeostasis in fasting northern elephant seals (Mirounga angustirostris) measured by metabolomics analysis and standard methods

PubMed Central

Boaz, Segal M.; Champagne, Cory D.; Fowler, Melinda A.; Houser, Dorian H.; Crocker, Daniel E.

2011-01-01

Despite the importance of water-soluble vitamins to metabolism, there is limited knowledge of their serum availability in fasting wildlife. We evaluated changes in water-soluble vitamins in northern elephant seals, a species with an exceptional ability to withstand nutrient deprivation. We used a metabolomics approach to measure vitamins and associated metabolites under extended natural fasts for up to seven weeks in free-ranging lactating or developing seals. Water-soluble vitamins were not detected with this metabolomics platform, but could be measured with standard assays. Concentrations of measured vitamins varied independently, but all were maintained at detectable levels over extended fasts, suggesting that defense of vitamin levels is a component of fasting adaptation in the seals. Metabolomics was not ideal for generating complete vitamin profiles in this species, but gave novel insights into vitamin metabolism by detecting key related metabolites. For example, niacin level reductions in lactating females were associated with significant reductions in precursors suggesting downregulation of the niacin synthetic pathway. The ability to detect individual vitamins using metabolomics may be impacted by the large number of novel compounds detected. Modifications to the analysis platforms and compound detection algorithms used in this study may be required for improving water-soluble vitamin detection in this and other novel wildlife systems. PMID:21983145

KEGG Bioinformatics Resource for Plant Genomics and Metabolomics.

PubMed

Kanehisa, Minoru

2016-01-01

In the era of high-throughput biology it is necessary to develop not only elaborate computational methods but also well-curated databases that can be used as reference for data interpretation. KEGG ( http://www.kegg.jp/ ) is such a reference knowledge base with two specific aims. One is to compile knowledge on high-level functions of the cell and the organism in terms of the molecular interaction and reaction networks, which is implemented in KEGG pathway maps, BRITE functional hierarchies, and KEGG modules. The other is to expand knowledge on genes and proteins involved in the molecular networks from experimentally observed organisms to other organisms using the concept of orthologs, which is implemented in the KEGG Orthology (KO) system. Thus, KEGG is a generic resource applicable to all organisms and enables interpretation of high-level functions from genomic and molecular data. Here we first present a brief overview of the entire KEGG resource, and then give an introduction of how to use KEGG in plant genomics and metabolomics research.

Can NMR solve some significant challenges in metabolomics?

PubMed Central

Gowda, G.A. Nagana; Raftery, Daniel

2015-01-01

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

A Lipidomic and Metabolomic Serum Signature from Nonhuman Primates Exposed to Ionizing Radiation.

PubMed

Pannkuk, Evan L; Laiakis, Evagelia C; Mak, Tytus D; Astarita, Giuseppe; Authier, Simon; Wong, Karen; Fornace, Albert J

2016-05-01

Due to dangers associated with potential accidents from nuclear energy and terrorist threats, there is a need for high-throughput biodosimetry to rapidly assess individual doses of radiation exposure. Lipidomics and metabolomics are becoming common tools for determining global signatures after disease or other physical insult and provide a "snapshot" of potential cellular damage. The current study assesses changes in the nonhuman primate (NHP) serum lipidome and metabolome 7 days following exposure to ionizing radiation (IR). Serum sample lipids and metabolites were extracted using a biphasic liquid-liquid extraction and analyzed by ultra performance liquid chromatography quadrupole time-of-flight mass spectrometry. Global radiation signatures were acquired in data-independent mode. Radiation exposure caused significant perturbations in lipid metabolism, affecting all major lipid species, including free fatty acids, glycerolipids, glycerophospholipids and esterified sterols. In particular, we observed a significant increase in the levels of polyunsaturated fatty acids (PUFA)-containing lipids in the serum of NHPs exposed to 10 Gy radiation, suggesting a primary role played by PUFAs in the physiological response to IR. Metabolomics profiling indicated an increase in the levels of amino acids, carnitine, and purine metabolites in the serum of NHPs exposed to 10 Gy radiation, suggesting perturbations to protein digestion/absorption, biological oxidations, and fatty acid β-oxidation. This is the first report to determine changes in the global NHP serum lipidome and metabolome following radiation exposure and provides information for developing metabolomic biomarker panels in human-based biodosimetry.

Can NMR solve some significant challenges in metabolomics?

NASA Astrophysics Data System (ADS)

Nagana Gowda, G. A.; Raftery, Daniel

2015-11-01

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

Nuclear magnetic resonance (NMR)-based metabolomics for cancer research.

PubMed

Ranjan, Renuka; Sinha, Neeraj

2018-05-07

Nuclear magnetic resonance (NMR) has emerged as an effective tool in various spheres of biomedical research, amongst which metabolomics is an important method for the study of various types of disease. Metabolomics has proved its stronghold in cancer research by the development of different NMR methods over time for the study of metabolites, thus identifying key players in the aetiology of cancer. A plethora of one-dimensional and two-dimensional NMR experiments (in solids, semi-solids and solution phases) are utilized to obtain metabolic profiles of biofluids, cell extracts and tissue biopsy samples, which can further be subjected to statistical analysis. Any alteration in the assigned metabolite peaks gives an indication of changes in metabolic pathways. These defined changes demonstrate the utility of NMR in the early diagnosis of cancer and provide further measures to combat malignancy and its progression. This review provides a snapshot of the trending NMR techniques and the statistical analysis involved in the metabolomics of diseases, with emphasis on advances in NMR methodology developed for cancer research. Copyright © 2018 John Wiley & Sons, Ltd.

Evaluation of Cancer Metabolomics Using ex vivo High Resolution Magic Angle Spinning (HRMAS) Magnetic Resonance Spectroscopy (MRS)

PubMed Central

Fuss, Taylor L.; Cheng, Leo L.

2016-01-01

According to World Health Organization (WHO) estimates, cancer is responsible for more deaths than all coronary heart disease or stroke worldwide, serving as a major public health threat around the world. High resolution magic angle spinning (HRMAS) magnetic resonance spectroscopy (MRS) has demonstrated its usefulness in the identification of cancer metabolic markers with the potential to improve diagnosis and prognosis for the oncology clinic, due partially to its ability to preserve tissue architecture for subsequent histological and molecular pathology analysis. Capable of the quantification of individual metabolites, ratios of metabolites, and entire metabolomic profiles, HRMAS MRS is one of the major techniques now used in cancer metabolomic research. This article reviews and discusses literature reports of HRMAS MRS studies of cancer metabolomics published between 2010 and 2015 according to anatomical origins, including brain, breast, prostate, lung, gastrointestinal, and neuroendocrine cancers. These studies focused on improving diagnosis and understanding patient prognostication, monitoring treatment effects, as well as correlating with the use of in vivo MRS in cancer clinics. PMID:27011205

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

PubMed

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

2017-07-01

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

Monitoring Ecological Impacts of Environmental Surface ...

EPA Pesticide Factsheets

Optimized cell-based metabolomics has been used to study the impacts of contaminants in surface waters on human and fish metabolomes. This method has proven to be resource- and time-effective, as well as sustainable for long term and large scale studies. In the current study, cell-based metabolomics is used to investigate the impacts of contaminants in surface waters on biological pathways in human and ecologically relevant cell lines. Water samples were collected from stream sites nationwide, where significant impacts have been estimated from the most potentially contaminated sources (i.e. waste water treatment plants, concentrated animal feeding operations, mining operations, and plant-based agricultural operations that use intensive chemical applications). Zebrafish liver cells (ZFL) were used to study exposure impacts on in vitro metabolomes. In addition, a small number of water samples were studied using two human cell lines (liver cells, HepG2 and brain cells, LN229). The cellular metabolites were profiled by nuclear magnetic resonance (NMR) spectroscopy and gas chromatography mass spectrometry (GC-MS). Detailed methods and results will be reported. Presented at SETAC North America 37th Annual Meeting

Combined metabolomic and correlation networks analyses reveal fumarase insufficiency altered amino acid metabolism.

PubMed

Hou, Entai; Li, Xian; Liu, Zerong; Zhang, Fuchang; Tian, Zhongmin

2018-04-01

Fumarase catalyzes the interconversion of fumarate and l-malate in the tricarboxylic acid cycle. Fumarase insufficiencies were associated with increased levels of fumarate, decreased levels of malate and exacerbated salt-induced hypertension. To gain insights into the metabolism profiles induced by fumarase insufficiency and identify key regulatory metabolites, we applied a GC-MS based metabolomics platform coupled with a network approach to analyze fumarase insufficient human umbilical vein endothelial cells (HUVEC) and negative controls. A total of 24 altered metabolites involved in seven metabolic pathways were identified as significantly altered, and enriched for the biological module of amino acids metabolism. In addition, Pearson correlation network analysis revealed that fumaric acid, l-malic acid, l-aspartic acid, glycine and l-glutamic acid were hub metabolites according to Pagerank based on their three centrality indices. Alanine aminotransferase and glutamate dehydrogenase activities increased significantly in fumarase deficiency HUVEC. These results confirmed that fumarase insufficiency altered amino acid metabolism. The combination of metabolomics and network methods would provide another perspective on expounding the molecular mechanism at metabolomics level. Copyright © 2017 John Wiley & Sons, Ltd.

Analysis of salivary phenotypes of generalized aggressive and chronic periodontitis through nuclear magnetic resonance-based metabolomics.

PubMed

Romano, Federica; Meoni, Gaia; Manavella, Valeria; Baima, Giacomo; Tenori, Leonardo; Cacciatore, Stefano; Aimetti, Mario

2018-06-07

Recent findings about the differential gene expression signature of periodontal lesions have raised the hypothesis of distinctive biological phenotypes expressed by generalized chronic periodontitis (GCP) and generalized aggressive periodontitis (GAgP) patients. Therefore, this cross-sectional investigation was planned, primarily, to determine the ability of nuclear magnetic resonance (NMR) spectroscopic analysis of unstimulated whole saliva to discriminate GCP and GAgP disease-specific metabolomic fingerprint and, secondarily, to assess potential metabolites discriminating periodontitis patients from periodontally healthy individuals (HI). NMR-metabolomics spectra were acquired from salivary samples of patients with a clinical diagnosis of GCP (n = 33) or GAgP (n = 28) and from HI (n = 39). The clustering of HI, GCP and GAgP patients was achieved by using a combination of the Principal Component Analysis and Canonical Correlation Analysis on the NMR profiles. These analyses revealed a significant predictive accuracy discriminating HI from GCP, and discriminating HI from GAgP patients (both 81%). In contrast, the GAgP and GCP saliva samples seem to belong to the same metabolic space (60% predictive accuracy). Significantly lower levels (P < 0.05) of pyruvate, N-acetyl groups and lactate and higher levels (P < 0.05) of proline, phenylalanine, and tyrosine were found in GCP and GAgP patients compared with HI. Within the limitations of this study, CGP and GAgP metabolomic profiles were not unequivocally discriminated through a NMR-based spectroscopic analysis of saliva. This article is protected by copyright. All rights reserved. This article is protected by copyright. All rights reserved.

Microfluidics meets metabolomics to reveal the impact of Campylobacter jejuni infection on biochemical pathways.

PubMed

Mortensen, Ninell P; Mercier, Kelly A; McRitchie, Susan; Cavallo, Tammy B; Pathmasiri, Wimal; Stewart, Delisha; Sumner, Susan J

2016-06-01

Microfluidic devices that are currently being used in pharmaceutical research also have a significant potential for utilization in investigating exposure to infectious agents. We have established a microfluidic device cultured with Caco-2 cells, and utilized metabolomics to investigate the biochemical responses to the bacterial pathogen Campylobacter jejuni. In the microfluidic devices, Caco-2 cells polarize at day 5, are uniform, have defined brush borders and tight junctions, and form a mucus layer. Metabolomics analysis of cell culture media collected from both Caco-2 cell culture systems demonstrated a more metabolic homogenous biochemical profile in the media collected from microfluidic devices, compared with media collected from transwells. GeneGo pathway mapping indicated that aminoacyl-tRNA biosynthesis was perturbed by fluid flow, suggesting that fluid dynamics and shear stress impacts the cells translational quality control. Both microfluidic device and transwell culturing systems were used to investigate the impact of Campylobacter jejuni infection on biochemical processes. Caco-2 cells cultured in either system were infected at day 5 with C. jejuni 81-176 for 48 h. Metabolomics analysis clearly differentiated C. jejuni 81-176 infected and non-infected medias collected from the microfluidic devices, and demonstrated that C. jejuni 81-176 infection in microfluidic devices impacts branched-chain amino acid metabolism, glycolysis, and gluconeogenesis. In contrast, no distinction was seen in the biochemical profiles of infected versus non-infected media collected from cells cultured in transwells. Microfluidic culturing conditions demonstrated a more metabolically homogenous cell population, and present the opportunity for studying host-pathogen interactions for extended periods of time.

Microfluidics Meets Metabolomics to Reveal the Impact of Campylobacter jejuni Infection on Biochemical Pathways

PubMed Central

Mortensen, Ninell P.; Mercier, Kelly A.; McRitchie, Susan; Cavallo, Tammy B.; Pathmasiri, Wimal; Stewart, Delisha; Sumner, Susan J.

2016-01-01

Microfluidic devices that are currently being used in pharmaceutical research also have a significant potential for utilization in investigating exposure to infectious agents. We have established a microfluidic device cultured with Caco-2 cells, and utilized metabolomics to investigate the biochemical responses to the bacterial pathogen Campylobacter jejuni. In the microfluidic devices, Caco-2 cells polarize at day 5, are uniform, have defined brush borders and tight junctions, and form a mucus layer. Metabolomics analysis of cell culture media collected from both Caco-2 cell culture systems demonstrated a more metabolic homogenous biochemical profile in the media collected from microfluidic devices, compared with media collected from transwells. GeneGo pathway mapping indicated that aminoacyl-tRNA biosynthesis was perturbed by fluid flow, suggesting that fluid dynamics and shear stress impacts the cells translational quality control. Both microfluidic device and transwell culturing systems were used to investigate the impact of Campylobacter jejuni infection on biochemical processes. Caco-2 cells cultured in either system were infected at day 5 with C. jejuni 81-176 for 48 hours. Metabolomics analysis clearly differentiated C. jejuni 81-176 infected and non-infected medias collected from the microfluidic devices, and demonstrated that C. jejuni 81-176 infection in microfluidic devices impacts branched-chain amino acid metabolism, glycolysis, and gluconeogenesis. In contrast, no distinction was seen in the biochemical profiles of infected versus non-infected media collected from cells cultured in transwells. Microfluidic culturing conditions demonstrated a more metabolically homogenous cell population, and present the opportunity for studying host-pathogen interactions for extended periods of time. PMID:27231016

Metabolomic signatures of aggressive prostate cancer.

PubMed

McDunn, Jonathan E; Li, Zhen; Adam, Klaus-Peter; Neri, Bruce P; Wolfert, Robert L; Milburn, Michael V; Lotan, Yair; Wheeler, Thomas M

2013-10-01

Current diagnostic techniques have increased the detection of prostate cancer; however, these tools inadequately stratify patients to minimize mortality. Recent studies have identified a biochemical signature of prostate cancer metastasis, including increased sarcosine abundance. This study examined the association of tissue metabolites with other clinically significant findings. A state of the art metabolomics platform analyzed prostatectomy tissues (331 prostate tumor, 178 cancer-free prostate tissues) from two independent sites. Biochemicals were analyzed by gas chromatography-mass spectrometry and ultrahigh performance liquid chromatography-tandem mass spectrometry. Statistical analyses identified metabolites associated with cancer aggressiveness: Gleason score, extracapsular extension, and seminal vesicle and lymph node involvement. Prostate tumors had significantly altered metabolite profiles compared to cancer-free prostate tissues, including biochemicals associated with cell growth, energetics, stress, and loss of prostate-specific biochemistry. Many metabolites were further associated with clinical findings of aggressive disease. Aggressiveness-associated metabolites stratified prostate tumor tissues with high abundances of compounds associated with normal prostate function (e.g., citrate and polyamines) from more clinically advanced prostate tumors. These aggressive prostate tumors were further subdivided by abundance profiles of metabolites including NAD+ and kynurenine. When added to multiparametric nomograms, metabolites improved prediction of organ confinement (AUROC from 0.53 to 0.62) and 5-year recurrence (AUROC from 0.53 to 0.64). These findings support and extend earlier metabolomic studies in prostate cancer and studies where metabolic enzymes have been associated with carcinogenesis and/or outcome. Furthermore, these data suggest that panels of analytes may be valuable to translate metabolomic findings to clinically useful diagnostic tests. Copyright © 2013 Wiley Periodicals, Inc.

Lactation is associated with altered metabolomic signatures in women with gestational diabetes.

PubMed

Much, Daniela; Beyerlein, Andreas; Kindt, Alida; Krumsiek, Jan; Stückler, Ferdinand; Rossbauer, Michaela; Hofelich, Anna; Wiesenäcker, David; Hivner, Susanne; Herbst, Melanie; Römisch-Margl, Werner; Prehn, Cornelia; Adamski, Jerzy; Kastenmüller, Gabi; Theis, Fabian; Ziegler, Anette-G; Hummel, Sandra

2016-10-01

Lactation for >3 months in women with gestational diabetes is associated with a reduced risk of type 2 diabetes that persists for up to 15 years postpartum. However, the underlying mechanisms are unknown. We examined whether in women with gestational diabetes lactation for >3 months is associated with altered metabolomic signatures postpartum. We enrolled 197 women with gestational diabetes at a median of 3.6 years (interquartile range 0.7-6.5 years) after delivery. Targeted metabolomics profiles (including 156 metabolites) were obtained during a glucose challenge test. Comparisons of metabolite concentrations and ratios between women who lactated for >3 months and women who lactated for ≤3 months or not at all were performed using linear regression with adjustment for age and BMI at the postpartum visit, time since delivery, and maternal education level, and correction for multiple testing. Gaussian graphical modelling was used to generate metabolite networks. Lactation for >3 months was associated with a higher total lysophosphatidylcholine/total phosphatidylcholine ratio; in women with short-term follow-up, it was also associated with lower leucine concentrations and a lower total branched-chain amino acid concentration. Gaussian graphical modelling identified subgroups of closely linked metabolites within phosphatidylcholines and branched-chain amino acids that were affected by lactation for >3 months and have been linked to the pathophysiology of type 2 diabetes in previous studies. Lactation for >3 months in women with gestational diabetes is associated with changes in the metabolomics profile that have been linked to the early pathogenesis of type 2 diabetes.

Comparisons of large (Vaccinium macrocarpon Ait.) and small (Vaccinium oxycoccos L., Vaccinium vitis-idaea L.) cranberry in British Columbia by phytochemical determination, antioxidant potential, and metabolomic profiling with chemometric analysis.

PubMed

Brown, Paula N; Turi, Christina E; Shipley, Paul R; Murch, Susan J

2012-04-01

There is a long history of use and modern commercial importance of large and small cranberries in North America. The central objective of the current research was to characterize and compare the chemical composition of 2 west coast small cranberry species traditionally used (Vaccinium oxycoccos L. and Vaccinium vitis-idaea L.) with the commercially cultivated large cranberry (Vaccinium macrocarpon Ait.) indigenous to the east coast of North America. V. oxycoccos and V. macrocarpon contained the 5 major anthocyanins known in cranberry; however, the ratio of glycosylated peonidins to cyanidins varied, and V. vitis-idaea did not contain measurable amounts of glycosylated peonidins. Extracts of all three berries were found to contain serotonin, melatonin, and ascorbic acid. Antioxidant activity was not found to correlate with indolamine levels while anthocyanin content showed a negative correlation, and vitamin C content positively correlated. From the metabolomics profiles, 4624 compounds were found conserved across V. macrocarpon, V. oxycoccoS, and V. vitis-idaea with a total of approximately 8000-10 000 phytochemicals detected in each species. From significance analysis, it was found that 2 compounds in V. macrocarpoN, 3 in V. oxycoccos, and 5 in V. vitis-idaea were key to the characterization and differentiation of these cranberry metabolomes. Through multivariate modeling, differentiation of the species was observed, and univariate statistical analysis was employed to provide a quality assessment of the models developed for the metabolomics data. © Georg Thieme Verlag KG Stuttgart · New York.

Integrated transcriptomics and metabolomics decipher differences in the resistance of pedunculate oak to the herbivore Tortrix viridana L.

PubMed Central

2013-01-01

Background The interaction between insect pests and their host plants is a never-ending race of evolutionary adaption. Plants have developed an armament against insect herbivore attacks, and attackers continuously learn how to address it. Using a combined transcriptomic and metabolomic approach, we investigated the molecular and biochemical differences between Quercus robur L. trees that resisted (defined as resistant oak type) or were susceptible (defined as susceptible oak type) to infestation by the major oak pest, Tortrix viridana L. Results Next generation RNA sequencing revealed hundreds of genes that exhibited constitutive and/or inducible differential expression in the resistant oak compared to the susceptible oak. Distinct differences were found in the transcript levels and the metabolic content with regard to tannins, flavonoids, and terpenoids, which are compounds involved in the defence against insect pests. The results of our transcriptomic and metabolomic analyses are in agreement with those of a previous study in which we showed that female moths prefer susceptible oaks due to their specific profile of herbivore-induced volatiles. These data therefore define two oak genotypes that clearly differ on the transcriptomic and metabolomic levels, as reflected by their specific defensive compound profiles. Conclusions We conclude that the resistant oak type seem to prefer a strategy of constitutive defence responses in contrast to more induced defence responses of the susceptible oaks triggered by feeding. These results pave the way for the development of biomarkers for an early determination of potentially green oak leaf roller-resistant genotypes in natural pedunculate oak populations in Europe. PMID:24160444

Defects in Mitochondrial Dynamics and Metabolomic Signatures of Evolving Energetic Stress in Mouse Models of Familial Alzheimer's Disease

PubMed Central

Trushina, Eugenia; Nemutlu, Emirhan; Zhang, Song; Christensen, Trace; Camp, Jon; Mesa, Janny; Siddiqui, Ammar; Tamura, Yasushi; Sesaki, Hiromi; Wengenack, Thomas M.; Dzeja, Petras P.; Poduslo, Joseph F.

2012-01-01

Background The identification of early mechanisms underlying Alzheimer's Disease (AD) and associated biomarkers could advance development of new therapies and improve monitoring and predicting of AD progression. Mitochondrial dysfunction has been suggested to underlie AD pathophysiology, however, no comprehensive study exists that evaluates the effect of different familial AD (FAD) mutations on mitochondrial function, dynamics, and brain energetics. Methods and Findings We characterized early mitochondrial dysfunction and metabolomic signatures of energetic stress in three commonly used transgenic mouse models of FAD. Assessment of mitochondrial motility, distribution, dynamics, morphology, and metabolomic profiling revealed the specific effect of each FAD mutation on the development of mitochondrial stress and dysfunction. Inhibition of mitochondrial trafficking was characteristic for embryonic neurons from mice expressing mutant human presenilin 1, PS1(M146L) and the double mutation of human amyloid precursor protein APP(Tg2576) and PS1(M146L) contributing to the increased susceptibility of neurons to excitotoxic cell death. Significant changes in mitochondrial morphology were detected in APP and APP/PS1 mice. All three FAD models demonstrated a loss of the integrity of synaptic mitochondria and energy production. Metabolomic profiling revealed mutation-specific changes in the levels of metabolites reflecting altered energy metabolism and mitochondrial dysfunction in brains of FAD mice. Metabolic biomarkers adequately reflected gender differences similar to that reported for AD patients and correlated well with the biomarkers currently used for diagnosis in humans. Conclusions Mutation-specific alterations in mitochondrial dynamics, morphology and function in FAD mice occurred prior to the onset of memory and neurological phenotype and before the formation of amyloid deposits. Metabolomic signatures of mitochondrial stress and altered energy metabolism indicated alterations in nucleotide, Krebs cycle, energy transfer, carbohydrate, neurotransmitter, and amino acid metabolic pathways. Mitochondrial dysfunction, therefore, is an underlying event in AD progression, and FAD mouse models provide valuable tools to study early molecular mechanisms implicated in AD. PMID:22393443

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).

PubMed

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 monitoring and may provide insight into the progression of this and other insidious diseases.

Serum Metabolomic Profiles in Neonatal Mice following Oral Brominated Flame Retardant Exposures to Hexabromocyclododecane (HBCD) Alpha, Gamma, and Commercial Mixture

PubMed Central

Szabo, David T.; Pathmasiri, Wimal; Sumner, Susan; Birnbaum, Linda S.

2016-01-01

Background: Hexabromocyclododecane (HBCD) is a high production volume brominated flame retardant added to building insulation foams, electronics, and textiles. HBCD is a commercial mixture (CM-HBCD) composed of three main stereoisomers: α-HBCD (10%), β-HBCD (10%), and γ-HBCD (80%). A shift from the dominant stereoisomer γ-HBCD to α-HBCD is detected in humans and wildlife. Objectives: Considering CM-HBCD has been implicated in neurodevelopment and endocrine disruption, with expected metabolism perturbations, we performed metabolomics on mice serum obtained during a window-of-developmental neurotoxicity to draw correlations between early-life exposures and developmental outcomes and to predict health risks. Methods: Six female C57BL/6 mice at postnatal day (PND) 10 were administered a single gavage dose of α-, γ-, or CM-HBCD at 3, 10, and 30 mg/kg. Nuclear magnetic resonance metabolomics was used to analyze 60 μL serum aliquots of blood collected 4 days post-oral exposure. Results: Infantile mice exposed to α-, γ-, or CM-HBCD demonstrated differences in endogenous metabolites by treatment and dose groups, including metabolites involved in glycolysis, gluconeogenesis, lipid metabolism, citric acid cycle, and neurodevelopment. Ketone bodies, 3-hydroxybutyrate, and acetoacetate, were nonstatistically elevated, when compared with mean control levels, in all treatment and dose groups, while glucose, pyruvate, and alanine varied. Acetoacetate was significantly increased in the 10 mg/kg α-HBCD and was nonsignificantly decreased with CM-HBCD. A third ketone body, acetone, was significantly lower in the 30 mg/kg α-HBCD group with significant increases in pyruvate at the same treatment and dose group. Metabolites significant in differentiating treatment and dose groups were also identified, including decreases in amino acids glutamate (excitatory neurotransmitter in learning and memory) and phenylalanine (neurotransmitter precursor) after α-HBCD and γ-HBCD exposure, respectively. Conclusions: We demonstrated that 4 days following a single neonatal oral exposure to α-, γ-, and CM-HBCD resulted in different serum metabolomic profiles, indicating stereoisomer- and mixture-specific effects and possible mechanisms of action. Citation: Szabo DT, Pathmasiri W, Sumner S, Birnbaum LS. 2017. Serum metabolomic profiles in neonatal mice following oral brominated flame retardant exposures to hexabromocyclododecane (HBCD) alpha, gamma, and commercial mixture. Environ Health Perspect 125:651–659; http://dx.doi.org/10.1289/EHP242 PMID:27814246

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

PubMed

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

2015-10-01

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

Metabolic profiling and enzyme analyses indicate a potential role of antioxidant systems in complementing glyphosate resistance in an Amaranthus palmeri biotype

USDA-ARS?s Scientific Manuscript database

Targeted metabolomic profiling and biochemical assays were employed to identify metabolite-level perturbations induced by glyphosate in susceptible (S) and resistant (R) biotypes of Amaranthus palmeri. Plants were treated with 0.4 kg ae ha-1 glyphosate and tissues were harvested at 8 and 72 hours af...

Metabolite profiling of a NIST Standard Reference Material for human plasma (SRM 1950): GC-MS, LC-MS, NMR, and clinical laboratory analyses, libraries, and web-based resources.

PubMed

Simón-Manso, Yamil; Lowenthal, Mark S; Kilpatrick, Lisa E; Sampson, Maureen L; Telu, Kelly H; Rudnick, Paul A; Mallard, W Gary; Bearden, Daniel W; Schock, Tracey B; Tchekhovskoi, Dmitrii V; Blonder, Niksa; Yan, Xinjian; Liang, Yuxue; Zheng, Yufang; Wallace, William E; Neta, Pedatsur; Phinney, Karen W; Remaley, Alan T; Stein, Stephen E

2013-12-17

Recent progress in metabolomics and the development of increasingly sensitive analytical techniques have renewed interest in global profiling, i.e., semiquantitative monitoring of all chemical constituents of biological fluids. In this work, we have performed global profiling of NIST SRM 1950, "Metabolites in Human Plasma", using GC-MS, LC-MS, and NMR. Metabolome coverage, difficulties, and reproducibility of the experiments on each platform are discussed. A total of 353 metabolites have been identified in this material. GC-MS provides 65 unique identifications, and most of the identifications from NMR overlap with the LC-MS identifications, except for some small sugars that are not directly found by LC-MS. Also, repeatability and intermediate precision analyses show that the SRM 1950 profiling is reproducible enough to consider this material as a good choice to distinguish between analytical and biological variability. Clinical laboratory data shows that most results are within the reference ranges for each assay. In-house computational tools have been developed or modified for MS data processing and interactive web display. All data and programs are freely available online at http://peptide.nist.gov/ and http://srmd.nist.gov/ .

Metabolite Profiling of Low-P Tolerant and Low-P Sensitive Maize Genotypes under Phosphorus Starvation and Restoration Conditions

PubMed Central

Ganie, Arshid Hussain; Ahmad, Altaf; Pandey, Renu; Aref, Ibrahim M.; Yousuf, Peerzada Yasir; Ahmad, Sayeed; Iqbal, Muhammad

2015-01-01

Background Maize (Zea mays L.) is one of the most widely cultivated crop plants. Unavoidable economic and environmental problems associated with the excessive use of phosphatic fertilizers demands its better management. The solution lies in improving the phosphorus (P) use efficiency to sustain productivity even at low P levels. Untargeted metabolomic profiling of contrasting genotypes provides a snap shot of whole metabolome which differs under specific conditions. This information provides an understanding of the mechanisms underlying tolerance to P stress and the approach for increasing P-use-efficiency. Methodology/Principal Findings A comparative metabolite-profiling approach based on gas chromatography-mass spectrometry (GC/MS) was applied to investigate the effect of P starvation and its restoration in low-P sensitive (HM-4) and low-P tolerant (PEHM-2) maize genotypes. A comparison of the metabolite profiles of contrasting genotypes in response to P-deficiency revealed distinct differences among low-P sensitive and tolerant genotypes. Another set of these genotypes were grown under P-restoration condition and sampled at different time intervals (3, 5 and 10 days) to investigate if the changes in metabolite profile under P-deficiency was restored. Significant variations in the metabolite pools of these genotypes were observed under P-deficiency which were genotype specific. Out of 180 distinct analytes, 91 were identified. Phosphorus-starvation resulted in accumulation of di- and trisaccharides and metabolites of ammonium metabolism, specifically in leaves, but decreased the levels of phosphate-containing metabolites and organic acids. A sharp increase in the concentrations of glutamine, asparagine, serine and glycine was observed in both shoots and roots under low-P condition. Conclusion The new insights generated on the maize metabolome in resposne to P-starvation and restoration would be useful towards improvement of the P-use efficiency in maize. PMID:26090681

Omics, microbial modeling, and food safety information infrastructure: a food safety perspective

USDA-ARS?s Scientific Manuscript database

Over the last three decades, advances in a variety of cutting-edge “omics” technologies, including genomics, proteomics, and metabolomics, as well as in molecular and mathematical modeling approaches have provided the ability to more easily determine and interpret the mechanisms underlying pathogene...

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

PubMed

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

2016-09-01

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

Metabolomic tools for secondary metabolite discovery from marine microbial symbionts.

PubMed

Macintyre, Lynsey; Zhang, Tong; Viegelmann, Christina; Martinez, Ignacio Juarez; Cheng, Cheng; Dowdells, Catherine; Abdelmohsen, Usama Ramadam; Gernert, Christine; Hentschel, Ute; Edrada-Ebel, RuAngelie

2014-06-05

Marine invertebrate-associated symbiotic bacteria produce a plethora of novel secondary metabolites which may be structurally unique with interesting pharmacological properties. Selection of strains usually relies on literature searching, genetic screening and bioactivity results, often without considering the chemical novelty and abundance of secondary metabolites being produced by the microorganism until the time-consuming bioassay-guided isolation stages. To fast track the selection process, metabolomic tools were used to aid strain selection by investigating differences in the chemical profiles of 77 bacterial extracts isolated from cold water marine invertebrates from Orkney, Scotland using liquid chromatography-high resolution mass spectrometry (LC-HRMS) and nuclear magnetic resonance (NMR) spectroscopy. Following mass spectrometric analysis and dereplication using an Excel macro developed in-house, principal component analysis (PCA) was employed to differentiate the bacterial strains based on their chemical profiles. NMR 1H and correlation spectroscopy (COSY) were also employed to obtain a chemical fingerprint of each bacterial strain and to confirm the presence of functional groups and spin systems. These results were then combined with taxonomic identification and bioassay screening data to identify three bacterial strains, namely Bacillus sp. 4117, Rhodococcus sp. ZS402 and Vibrio splendidus strain LGP32, to prioritize for scale-up based on their chemically interesting secondary metabolomes, established through dereplication and interesting bioactivities, determined from bioassay screening.

Systemic Metabolomic Changes in Blood Samples of Lung Cancer Patients Identified by Gas Chromatography Time-of-Flight Mass Spectrometry

PubMed Central

Miyamoto, Suzanne; Taylor, Sandra L.; Barupal, Dinesh K.; Taguchi, Ayumu; Wohlgemuth, Gert; Wikoff, William R.; Yoneda, Ken Y.; Gandara, David R.; Hanash, Samir M.; Kim, Kyoungmi; Fiehn, Oliver

2015-01-01

Lung cancer is a leading cause of cancer deaths worldwide. Metabolic alterations in tumor cells coupled with systemic indicators of the host response to tumor development have the potential to yield blood profiles with clinical utility for diagnosis and monitoring of treatment. We report results from two separate studies using gas chromatography time-of-flight mass spectrometry (GC-TOF MS) to profile metabolites in human blood samples that significantly differ from non-small cell lung cancer (NSCLC) adenocarcinoma and other lung cancer cases. Metabolomic analysis of blood samples from the two studies yielded a total of 437 metabolites, of which 148 were identified as known compounds and 289 identified as unknown compounds. Differential analysis identified 15 known metabolites in one study and 18 in a second study that were statistically different (p-values <0.05). Levels of maltose, palmitic acid, glycerol, ethanolamine, glutamic acid, and lactic acid were increased in cancer samples while amino acids tryptophan, lysine and histidine decreased. Many of the metabolites were found to be significantly different in both studies, suggesting that metabolomics appears to be robust enough to find systemic changes from lung cancer, thus showing the potential of this type of analysis for lung cancer detection. PMID:25859693

Untargeted Metabolomic Analysis of Rat Neuroblastoma Cells as a Model System to Study the Biochemical Effects of the Acute Administration of Methamphetamine.

PubMed

Maker, Garth L; Green, Tobias; Mullaney, Ian; Trengove, Robert D

2018-06-07

Methamphetamine is an illicit psychostimulant drug that is linked to a number of diseases of the nervous system. The downstream biochemical effects of its primary mechanisms are not well understood, and the objective of this study was to investigate whether untargeted metabolomic analysis of an in vitro model could generate data relevant to what is already known about this drug. Rat B50 neuroblastoma cells were treated with 1 mM methamphetamine for 48 h, and both intracellular and extracellular metabolites were profiled using gas chromatography⁻mass spectrometry. Principal component analysis of the data identified 35 metabolites that contributed most to the difference in metabolite profiles. Of these metabolites, the most notable changes were in amino acids, with significant increases observed in glutamate, aspartate and methionine, and decreases in phenylalanine and serine. The data demonstrated that glutamate release and, subsequently, excitotoxicity and oxidative stress were important in the response of the neuronal cell to methamphetamine. Following this, the cells appeared to engage amino acid-based mechanisms to reduce glutamate levels. The potential of untargeted metabolomic analysis has been highlighted, as it has generated biochemically relevant data and identified pathways significantly affected by methamphetamine. This combination of technologies has clear uses as a model for the study of neuronal toxicology.

Global Metabolic Regulation of the Snow Alga Chlamydomonas nivalis in Response to Nitrate or Phosphate Deprivation by a Metabolome Profile Analysis.

PubMed

Lu, Na; Chen, Jun-Hui; Wei, Dong; Chen, Feng; Chen, Gu

2016-05-10

In the present work, Chlamydomonas nivalis, a model species of snow algae, was used to illustrate the metabolic regulation mechanism of microalgae under nutrient deprivation stress. The seed culture was inoculated into the medium without nitrate or phosphate to reveal the cell responses by a metabolome profile analysis using gas chromatography time-of-flight mass spectrometry (GC/TOF-MS). One hundred and seventy-one of the identified metabolites clustered into five groups by the orthogonal partial least squares discriminant analysis (OPLS-DA) model. Among them, thirty of the metabolites in the nitrate-deprived group and thirty-nine of the metabolites in the phosphate-deprived group were selected and identified as "responding biomarkers" by this metabolomic approach. A significant change in the abundance of biomarkers indicated that the enhanced biosynthesis of carbohydrates and fatty acids coupled with the decreased biosynthesis of amino acids, N-compounds and organic acids in all the stress groups. The up- or down-regulation of these biomarkers in the metabolic network provides new insights into the global metabolic regulation and internal relationships within amino acid and fatty acid synthesis, glycolysis, the tricarboxylic acid cycle (TCA) and the Calvin cycle in the snow alga under nitrate or phosphate deprivation stress.

Metabolic responses of Quercus ilex seedlings to wounding analysed with nuclear magnetic resonance profiling.

PubMed

Sardans, J; Gargallo-Garriga, A; Pérez-Trujillo, M; Parella, T J; Seco, R; Filella, I; Peñuelas, J

2014-03-01

Plants defend themselves against herbivory at several levels. One of these is the synthesis of inducible chemical defences. Using NMR metabolomic techniques, we studied the metabolic changes of plant leaves after a wounding treatment simulating herbivore attack in the Mediterranean sclerophyllous tree Quercus ilex. First, an increase in glucose content was observed in wounded plants. There was also an increase in the content of C-rich secondary metabolites such as quinic acid and quercitol, both related to the shikimic acid pathway and linked to defence against biotic stress. There was also a shift in N-storing amino acids, from leucine and isoleucine to asparagine and choline. The observed higher content of asparagine is related to the higher content of choline through serine that was proved to be the precursor of choline. Choline is a general anti-herbivore and pathogen deterrent. The study shows the rapid metabolic response of Q. ilex in defending its leaves, based on a rapid increase in the production of quinic acid, quercitol and choline. The results also confirm the suitability of (1)H NMR-based metabolomic profiling studies to detect global metabolome shifts after wounding stress in tree leaves, and therefore its suitability in ecometabolomic studies. © 2013 German Botanical Society and The Royal Botanical Society of the Netherlands.

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

PubMed

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.

The Use of Functional Genomics in Conjunction with Metabolomics for Mycobacterium tuberculosis Research

PubMed Central

Swanepoel, Conrad C.

2014-01-01

Tuberculosis (TB), caused by Mycobacterium tuberculosis, is a fatal infectious disease, resulting in 1.4 million deaths globally per annum. Over the past three decades, genomic studies have been conducted in an attempt to elucidate the functionality of the genome of the pathogen. However, many aspects of this complex genome remain largely unexplored, as approaches like genomics, proteomics, and transcriptomics have failed to characterize them successfully. In turn, metabolomics, which is relatively new to the “omics” revolution, has shown great potential for investigating biological systems or their modifications. Furthermore, when these data are interpreted in combination with previously acquired genomics, proteomics and transcriptomics data, using what is termed a systems biology approach, a more holistic understanding of these systems can be achieved. In this review we discuss how metabolomics has contributed so far to characterizing TB, with emphasis on the resulting improved elucidation of M. tuberculosis in terms of (1) metabolism, (2) growth and replication, (3) pathogenicity, and (4) drug resistance, from the perspective of systems biology. PMID:24771957

Multiomics tools for the diagnosis and treatment of rare neurological disease.

PubMed

Crowther, L M; Poms, M; Plecko, Barbara

2018-05-01

Conventional workup of rare neurological disease is frequently hampered by diagnostic delay or lack of diagnosis. While biomarkers have been established for many neurometabolic disorders, improved methods are required for diagnosis of previously unidentified or underreported causes of rare neurological disease. This would result in a higher diagnostic yield and increased patient numbers required for interventional studies. Recent studies using next-generation sequencing and metabolomics have led to identification of novel disease-causing genes and biomarkers. This combined approach can assist in overcoming challenges associated with analyzing and interpreting the large amount of data obtained from each technique. In particular, metabolomics can support the pathogenicity of sequence variants in genes encoding enzymes or transporters involved in metabolic pathways. Moreover, metabolomics can show the broader perturbation caused by inborn errors of metabolism and identify a metabolic fingerprint of metabolic disorders. As such, using "omics" has great potential to meet the current needs for improved diagnosis and elucidation of rare neurological disease.

Metabolomic analysis of avocado fruits by GC-APCI-TOF MS: effects of ripening degrees and fruit varieties.

PubMed

Hurtado-Fernández, E; Pacchiarotta, T; Mayboroda, O A; Fernández-Gutiérrez, A; Carrasco-Pancorbo, A

2015-01-01

In order to investigate avocado fruit ripening, nontargeted GC-APCI-TOF MS metabolic profiling analyses were carried out. Principal component analysis (PCA) and partial least squares discriminant analysis (PLS-DA) were used to explore the metabolic profiles from fruit samples of 13 varieties at two different ripening degrees. Mannoheptulose; pentadecylfuran; aspartic, malic, stearic, citric and pantothenic acids; mannitol; and β-sitosterol were some of the metabolites found as more influential for the PLS-DA model. The similarities among genetically related samples (putative mutants of "Hass") and their metabolic differences from the rest of the varieties under study have also been evaluated. The achieved results reveal new insights into avocado fruit composition and metabolite changes, demonstrating therefore the value of metabolomics as a functional genomics tool in characterizing the mechanism of fruit ripening development, a key developmental stage in most economically important fruit crops.

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

PubMed

Niedenführ, Sebastian; ten Pierick, Angela; van Dam, Patricia T N; Suarez-Mendez, Camilo A; Nöh, Katharina; Wahl, S Aljoscha

2016-05-01

Fluxomics and metabolomics are crucial tools for metabolic engineering and biomedical analysis to determine the in vivo cellular state. Especially, the application of (13)C isotopes allows comprehensive insights into the functional operation of cellular metabolism. Compared to single MS, tandem mass spectrometry (MS/MS) provides more detailed and accurate measurements of the metabolite enrichment patterns (tandem mass isotopomers), increasing the accuracy of metabolite concentration measurements and metabolic flux estimation. MS-type data from isotope labeling experiments is biased by naturally occurring stable isotopes (C, H, N, O, etc.). In particular, GC-MS(/MS) requires derivatization for the usually non-volatile intracellular metabolites introducing additional natural isotopes leading to measurements that do not directly represent the carbon labeling distribution. To make full use of LC- and GC-MS/MS mass isotopomer measurements, the influence of natural isotopes has to be eliminated (corrected). Our correction approach is analyzed for the two most common applications; (13)C fluxomics and isotope dilution mass spectrometry (IDMS) based metabolomics. Natural isotopes can have an impact on the calculated flux distribution which strongly depends on the substrate labeling and the actual flux distribution. Second, we show that in IDMS based metabolomics natural isotopes lead to underestimated concentrations that can and should be corrected with a nonlinear calibration. Our simulations indicate that the correction for natural abundance in isotope based fluxomics and quantitative metabolomics is essential for correct data interpretation. © 2015 Wiley Periodicals, Inc.

Transmissible microbial and metabolomic remodeling by soluble dietary fiber improves metabolic homeostasis

PubMed Central

He, Baokun; Nohara, Kazunari; Ajami, Nadim J.; Michalek, Ryan D.; Tian, Xiangjun; Wong, Matthew; Losee-Olson, Susan H.; Petrosino, Joseph F.; Yoo, Seung-Hee; Shimomura, Kazuhiro; Chen, Zheng

2015-01-01

Dietary fibers are increasingly appreciated as beneficial nutritional components. However, a requisite role of gut microbiota in fiber function and the overall impact of fibers on metabolomic flux remain unclear. We herein showed enhancing effects of a soluble resistant maltodextrin (RM) on glucose homeostasis in mouse metabolic disease models. Remarkably, fecal microbiota transplantation (FMT) caused pronounced and time-dependent improvement in glucose tolerance in RM recipient mice, indicating a causal relationship between microbial remodeling and metabolic efficacy. Microbial 16S sequencing revealed transmissible taxonomic changes correlated with improved metabolism, notably enrichment of probiotics and reduction of Alistipes and Bacteroides known to associate with high fat/protein diets. Metabolomic profiling further illustrated broad changes, including enrichment of phenylpropionates and decreases in key intermediates of glucose utilization, cholesterol biosynthesis and amino acid fermentation. These studies elucidate beneficial roles of RM-dependent microbial remodeling in metabolic homeostasis, and showcase prevalent health-promoting potentials of dietary fibers. PMID:26040234

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

PubMed

Jones, Oliver A H; Hügel, Helmut M

2013-01-01

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

1H NMR-based metabolomic profiling for identification of metabolites in Capsicum annuum cv. mirasol infected by beet mild curly top virus (BMCTV).

PubMed

Villa-Ruano, Nemesio; Velásquez-Valle, Rodolfo; Zepeda-Vallejo, L Gerardo; Pérez-Hernández, Nury; Velázquez-Ponce, Manuel; Arcos-Adame, Victor M; Becerra-Martínez, Elvia

2018-04-01

Beet mild curly top virus (BMCTV) is associated with an outbreak of curly top in chili pepper, tomato and other Solanaceae species, which can cause severe crop losses. The aim of this work was to obtain the 1 H NMR metabolomic profiling of both healthy chili peppers (cv. mirasol) and infected chili peppers with BMCTV in order to find chemical markers associated to the infection process. Significant differences were found between the two groups, according to principal component analysis and orthogonal projections to latent structure discriminant analysis. Compared to the asymptomatic peppers, the symptomatic fruits had higher relative abundance of fructose, isoleucine, histidine, phenylalanine and tryptophan. Contrarily, the asymptomatic samples showed greater amounts of malonate and isobutyrate. These results suggest that in diseased chili peppers there are metabolic changes related to the viral acquisition of energy for replication and capsid assembly. This is the first study describing the chemical profiling of a polar extract obtained from Capsicum annuum infected by BMCTV under open field conditions. Copyright © 2018 Elsevier Ltd. All rights reserved.

Metabolomic profiling of doxycycline treatment in chronic obstructive pulmonary disease.

PubMed

Singh, Brajesh; Jana, Saikat K; Ghosh, Nilanjana; Das, Soumen K; Joshi, Mamata; Bhattacharyya, Parthasarathi; Chaudhury, Koel

2017-01-05

Serum metabolic profiling can identify the metabolites responsible for discrimination between doxycycline treated and untreated chronic obstructive pulmonary disease (COPD) and explain the possible effect of doxycycline in improving the disease conditions. 1 H nuclear magnetic resonance (NMR)-based metabolomics was used to obtain serum metabolic profiles of 60 add-on doxycycline treated COPD patients and 40 patients receiving standard therapy. The acquired data were analyzed using multivariate principal component analysis (PCA), partial least-squares-discriminant analysis (PLS-DA), and orthogonal projection to latent structure with discriminant analysis (OPLS-DA). A clear metabolic differentiation was apparent between the pre and post doxycycline treated group. The distinguishing metabolites lactate and fatty acids were significantly down-regulated and formate, citrate, imidazole and l-arginine upregulated. Lactate and folate are further validated biochemically. Metabolic changes, such as decreased lactate level, inhibited arginase activity and lowered fatty acid level observed in COPD patients in response to add-on doxycycline treatment, reflect the anti-inflammatory action of the drug. Doxycycline as a possible therapeutic option for COPD seems promising. Copyright © 2016 Elsevier B.V. All rights reserved.

Exploring the Role of Different Neonatal Nutrition Regimens during the First Week of Life by Urinary GC-MS Metabolomics

PubMed Central

Dessì, Angelica; Murgia, Antonio; Agostino, Rocco; Pattumelli, Maria Grazia; Schirru, Andrea; Scano, Paola; Fanos, Vassilios; Caboni, Pierluigi

2016-01-01

In this study, a gas-chromatography mass spectrometry (GC-MS) metabolomics study was applied to examine urine metabolite profiles of different classes of neonates under different nutrition regimens. The study population included 35 neonates, exclusively either breastfed or formula milk fed, in a seven-day timeframe. Urine samples were collected from intrauterine growth restriction (IUGR), large for gestational age (LGA), and appropriate gestational age (AGA) neonates. At birth, IUGR and LGA neonates showed similarities in their urine metabolite profiles that differed from AGA. When neonates started milk feeding, their metabolite excretion profile was strongly characterized by the different diet regimens. After three days of formula milk nutrition, urine had higher levels of glucose, galactose, glycine and myo-inositol, while up-regulated aconitic acid, aminomalonic acid and adipic acid were found in breast milk fed neonates. At seven days, neonates fed with formula milk shared higher levels of pseudouridine with IUGR and LGA at birth. Breastfed neonates shared up-regulated pyroglutamic acid, citric acid, and homoserine, with AGA at birth. The role of most important metabolites is herein discussed. PMID:26907266

Profiling the Oxylipin and Endocannabinoid Metabolome by UPLC-ESI-MS/MS in Human Plasma to Monitor Postprandial Inflammation.

PubMed

Gouveia-Figueira, Sandra; Späth, Jana; Zivkovic, Angela M; Nording, Malin L

2015-01-01

Bioactive lipids, including oxylipins, endocannabinoids, and related compounds may function as specific biochemical markers of certain aspects of inflammation. However, the postprandial responsiveness of these compounds is largely unknown; therefore, changes in the circulating oxylipin and endocannabinoid metabolome in response to a challenge meal were investigated at six occasions in a subject who freely modified her usual diet. The dietary change, and especially the challenge meal itself, represented a modification of precursor fatty acid status, with expectedly subtle effects on bioactive lipid levels. To detect even the slightest alteration, highly sensitive ultra-performance liquid chromatography (UPLC) coupled to electrospray ionization (ESI) tandem mass spectrometry (MS/MS) methods for bioactive lipid profiling was employed. A previously validated UPLC-ESI-MS/MS method for profiling the endocannabinoid metabolome was used, while validation of an UPLC-ESI-MS/MS method for oxylipin analysis was performed with acceptable outcomes for a majority of the parameters according to the US Food and Drug Administration guidelines for linearity (0.9938 < R2 < 0.9996), limit of detection (0.0005-2.1 pg on column), limit of quantification (0.0005-4.2 pg on column), inter- and intraday accuracy (85-115%) and precision (< 5%), recovery (40-109%) and stability (40-105%). Forty-seven of fifty-two bioactive lipids were detected in plasma samples at fasting and in the postprandial state (0.5, 1, and 3 hours after the meal). Multivariate analysis showed a significant shift of bioactive lipid profiles in the postprandial state due to inclusion of dairy products in the diet, which was in line with univariate analysis revealing seven compounds (NAGly, 9-HODE, 13-oxo-ODE, 9(10)-EpOME, 12(13)-EpOME, 20-HETE, and 11,12-DHET) that were significantly different between background diets in the postprandial state (but not at fasting). The only change in baseline levels at fasting was displayed by TXB2. Furthermore, postprandial responsiveness was detected for seven compounds (POEA, SEA, 9(10)-DiHOME, 12(13)-DiHOME, 13-oxo-ODE, 9-HODE, and 13-HODE). Hence, the data confirm that the UPLC-ESI-MS/MS method performance was sufficient to detect i) a shift, in the current case most notably in the postprandial bioactive lipid metabolome, caused by changes in diet and ii) responsiveness to a challenge meal for a subset of the oxylipin and endocannabinoid metabolome. To summarize, we have shown proof-of-concept of our UPLC-ESI-MS/MS bioactive lipid protocols for the purpose of monitoring subtle shifts, and thereby useful to address lipid-mediated postprandial inflammation.

Profiling the Oxylipin and Endocannabinoid Metabolome by UPLC-ESI-MS/MS in Human Plasma to Monitor Postprandial Inflammation

PubMed Central

Gouveia-Figueira, Sandra; Späth, Jana; Zivkovic, Angela M.; Nording, Malin L.

2015-01-01

Bioactive lipids, including oxylipins, endocannabinoids, and related compounds may function as specific biochemical markers of certain aspects of inflammation. However, the postprandial responsiveness of these compounds is largely unknown; therefore, changes in the circulating oxylipin and endocannabinoid metabolome in response to a challenge meal were investigated at six occasions in a subject who freely modified her usual diet. The dietary change, and especially the challenge meal itself, represented a modification of precursor fatty acid status, with expectedly subtle effects on bioactive lipid levels. To detect even the slightest alteration, highly sensitive ultra-performance liquid chromatography (UPLC) coupled to electrospray ionization (ESI) tandem mass spectrometry (MS/MS) methods for bioactive lipid profiling was employed. A previously validated UPLC-ESI-MS/MS method for profiling the endocannabinoid metabolome was used, while validation of an UPLC-ESI-MS/MS method for oxylipin analysis was performed with acceptable outcomes for a majority of the parameters according to the US Food and Drug Administration guidelines for linearity (0.9938 < R2 < 0.9996), limit of detection (0.0005–2.1 pg on column), limit of quantification (0.0005–4.2 pg on column), inter- and intraday accuracy (85–115%) and precision (< 5%), recovery (40–109%) and stability (40–105%). Forty-seven of fifty-two bioactive lipids were detected in plasma samples at fasting and in the postprandial state (0.5, 1, and 3 hours after the meal). Multivariate analysis showed a significant shift of bioactive lipid profiles in the postprandial state due to inclusion of dairy products in the diet, which was in line with univariate analysis revealing seven compounds (NAGly, 9-HODE, 13-oxo-ODE, 9(10)-EpOME, 12(13)-EpOME, 20-HETE, and 11,12-DHET) that were significantly different between background diets in the postprandial state (but not at fasting). The only change in baseline levels at fasting was displayed by TXB2. Furthermore, postprandial responsiveness was detected for seven compounds (POEA, SEA, 9(10)-DiHOME, 12(13)-DiHOME, 13-oxo-ODE, 9-HODE, and 13-HODE). Hence, the data confirm that the UPLC-ESI-MS/MS method performance was sufficient to detect i) a shift, in the current case most notably in the postprandial bioactive lipid metabolome, caused by changes in diet and ii) responsiveness to a challenge meal for a subset of the oxylipin and endocannabinoid metabolome. To summarize, we have shown proof-of-concept of our UPLC-ESI-MS/MS bioactive lipid protocols for the purpose of monitoring subtle shifts, and thereby useful to address lipid-mediated postprandial inflammation. PMID:26186333

Analysis of human plasma metabolites across different liquid chromatography/mass spectrometry platforms: Cross-platform transferable chemical signatures.

PubMed

Telu, Kelly H; Yan, Xinjian; Wallace, William E; Stein, Stephen E; Simón-Manso, Yamil

2016-03-15

The metabolite profiling of a NIST plasma Standard Reference Material (SRM 1950) on different liquid chromatography/mass spectrometry (LC/MS) platforms showed significant differences. Although these findings suggest caution when interpreting metabolomics results, the degree of overlap of both profiles allowed us to use tandem mass spectral libraries of recurrent spectra to evaluate to what extent these results are transferable across platforms and to develop cross-platform chemical signatures. Non-targeted global metabolite profiles of SRM 1950 were obtained on different LC/MS platforms using reversed-phase chromatography and different chromatographic scales (conventional HPLC, UHPLC and nanoLC). The data processing and the metabolite differential analysis were carried out using publically available (XCMS), proprietary (Mass Profiler Professional) and in-house software (NIST pipeline). Repeatability and intermediate precision showed that the non-targeted SRM 1950 profiling was highly reproducible when working on the same platform (relative standard deviation (RSD) <2%); however, substantial differences were found in the LC/MS patterns originating on different platforms or even using different chromatographic scales (conventional HPLC, UHPLC and nanoLC) on the same platform. A substantial degree of overlap (common molecular features) was also found. A procedure to generate consistent chemical signatures using tandem mass spectral libraries of recurrent spectra is proposed. Different platforms rendered significantly different metabolite profiles, but the results were highly reproducible when working within one platform. Tandem mass spectral libraries of recurrent spectra are proposed to evaluate the degree of transferability of chemical signatures generated on different platforms. Chemical signatures based on our procedure are most likely cross-platform transferable. Published in 2016. This article is a U.S. Government work and is in the public domain in the USA.

Assessing the metabolic effects of calcineurin inhibitors in renal transplant recipients by urine metabolic profiling.

PubMed

Diémé, Binta; Halimi, Jean Michel; Emond, Patrick; Büchler, Matthias; Nadal-Desbarat, Lydie; Blasco, Hélène; Le Guellec, Chantal

2014-07-27

Biomarkers that can predict graft function and/or renal side effects of calcineurin inhibitors (CNI) at each stage of treatment in kidney transplantation are still lacking. We report the first untargeted GC-MS-based metabolomic study on urines of renal transplant patients. This approach would bring insight in biomarkers useable for graft function monitoring. All consecutive patients receiving a kidney allograft in our transplantation department over a 6-month period were prospectively included and followed up for 12 months. We collected urine samples on the seventh day (D7) after transplantation, then at month 3 (M3) and month 12 (M12), and obtained mass-spectrometry-based urinary metabolic profiles. Multivariate analyses were conducted to compare metabolic profiles at the 3 different periods and to assess potential differences between cyclosporine and tacrolimus. Differences in metabolic signatures were also assessed according to graft function at D7 and renal function at M3 and M12. The urinary metabolic patterns varied over time in cyclosporine- and tacrolimus-treated patients and were somewhat different at D7, M3, and M12 between the 2 treatment groups. Principal metabolites that differed, regardless of the treatment used, were mainly sugars, inositol, and hippuric acid. Interestingly, among tacrolimus-treated patients, different metabolic signatures were found between patients with immediate or delayed graft function at D7. Urinary metabolomics represents a noninvasive way of monitoring immunosuppressive therapy in renal transplant patients. Although it is too early to consider it as a biomarker of CNI-induced injury or graft function, metabolomics appears a promising evaluation tool in this area.

Metabolomic Profiling in Individuals with a Failing Kidney Allograft

PubMed Central

Biancone, Luigi; Bussolino, Stefania; Merugumala, Sai; Tezza, Sara; D’Addio, Francesca; Ben Nasr, Moufida; Valderrama-Vasquez, Alessandro; Usuelli, Vera; De Zan, Valentina; El Essawy, Basset; Venturini, Massimo; Secchi, Antonio; De Cobelli, Francesco; Lin, Alexander; Chandraker, Anil; Fiorina, Paolo

2017-01-01

Background Alteration of certain metabolites may play a role in the pathophysiology of renal allograft disease. Methods To explore metabolomic abnormalities in individuals with a failing kidney allograft, we analyzed by liquid chromatography-mass spectrometry (LC-MS/MS; for ex vivo profiling of serum and urine) and two dimensional correlated spectroscopy (2D COSY; for in vivo study of the kidney graft) 40 subjects with varying degrees of chronic allograft dysfunction stratified by tertiles of glomerular filtration rate (GFR; T1, T2, T3). Ten healthy non-allograft individuals were chosen as controls. Results LC-MS/MS analysis revealed a dose-response association between GFR and serum concentration of tryptophan, glutamine, dimethylarginine isomers (asymmetric [A]DMA and symmetric [S]DMA) and short-chain acylcarnitines (C4 and C12), (test for trend: T1-T3 = p<0.05; p = 0.01; p<0.001; p = 0.01; p = 0.01; p<0.05, respectively). The same association was found between GFR and urinary levels of histidine, DOPA, dopamine, carnosine, SDMA and ADMA (test for trend: T1-T3 = p<0.05; p<0.01; p = 0.001; p<0.05; p = 0.001; p<0.001; p<0.01, respectively). In vivo 2D COSY of the kidney allograft revealed significant reduction in the parenchymal content of choline, creatine, taurine and threonine (all: p<0.05) in individuals with lower GFR levels. Conclusions We report an association between renal function and altered metabolomic profile in renal transplant individuals with different degrees of kidney graft function. PMID:28052095

Metabolic reprogramming of the urea cycle pathway in experimental pulmonary arterial hypertension rats induced by monocrotaline.

PubMed

Zheng, Hai-Kuo; Zhao, Jun-Han; Yan, Yi; Lian, Tian-Yu; Ye, Jue; Wang, Xiao-Jian; Wang, Zhe; Jing, Zhi-Cheng; He, Yang-Yang; Yang, Ping

2018-05-11

Pulmonary arterial hypertension (PAH) is a rare systemic disorder associated with considerable metabolic dysfunction. Although enormous metabolomic studies on PAH have been emerging, research remains lacking on metabolic reprogramming in experimental PAH models. We aim to evaluate the metabolic changes in PAH and provide new insight into endogenous metabolic disorders of PAH. A single subcutaneous injection of monocrotaline (MCT) (60 mg kg - 1 ) was used for rats to establish PAH model. Hemodynamics and right ventricular hypertrophy were adopted to evaluate the successful establishment of PAH model. Plasma samples were assessed through targeted metabolomic profiling platform to quantify 126 endogenous metabolites. Orthogonal partial least squares discriminant analysis (OPLS-DA) was used to discriminate between MCT-treated model and control groups. Metabolite Set Enrichment Analysis was adapted to exploit the most disturbed metabolic pathways. Endogenous metabolites of MCT treated PAH model and control group were well profiled using this platform. A total of 13 plasma metabolites were significantly altered between the two groups. Metabolite Set Enrichment Analysis highlighted that a disruption in the urea cycle pathway may contribute to PAH onset. Moreover, five novel potential biomarkers in the urea cycle, adenosine monophosphate, urea, 4-hydroxy-proline, ornithine, N-acetylornithine, and two candidate biomarkers, namely, O-acetylcarnitine and betaine, were found to be highly correlated with PAH. The present study suggests a new role of urea cycle disruption in the pathogenesis of PAH. We also found five urea cycle related biomarkers and another two candidate biomarkers to facilitate early diagnosis of PAH in metabolomic profile.

Can NMR solve some significant challenges in metabolomics?

PubMed

Nagana Gowda, G A; Raftery, Daniel

2015-11-01

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

Women with preterm birth have a distinct cervicovaginal metabolome.

PubMed

Ghartey, Jeny; Bastek, Jamie A; Brown, Amy G; Anglim, Laura; Elovitz, Michal A

2015-06-01

Metabolomics has the potential to reveal novel pathways involved in the pathogenesis of preterm birth (PTB). The objective of this study was to investigate whether the cervicovaginal (CV) metabolome was different in asymptomatic women destined to have a PTB compared with term birth. A nested case-control study was performed using CV fluid collected from a larger prospective cohort. The CV fluid was collected between 20-24 weeks (V1) and 24-28 weeks (V2). The metabolome was compared between women with a spontaneous PTB (n = 10) to women who delivered at term (n = 10). Samples were extracted and prepared for analysis using a standard extraction solvent method. Global biochemical profiles were determined using gas chromatography/mass spectrometry and ultra-performance liquid chromatography/tandem mass spectrometry. An ANOVA was used to detect differences in biochemical compounds between the groups. A false discovery rate was estimated to account for multiple comparisons. A total of 313 biochemicals were identified in CV fluid. Eighty-two biochemicals were different in the CV fluid at V1 in those destined to have a PTB compared with term birth, whereas 48 were different at V2. Amino acid, carbohydrate, and peptide metabolites were distinct between women with and without PTB. These data suggest that the CV space is metabolically active during pregnancy. Changes in the CV metabolome may be observed weeks, if not months, prior to any clinical symptoms. Understanding the CV metabolome may hold promise for unraveling the pathogenesis of PTB and may provide novel biomarkers to identify women most at risk. Copyright © 2015 Elsevier Inc. All rights reserved.

Lipidome and metabolome analysis of fresh tobacco leaves in different geographical regions using liquid chromatography-mass spectrometry.

PubMed

Li, Lili; Lu, Xin; Zhao, Jieyu; Zhang, Junjie; Zhao, Yanni; Zhao, Chunxia; Xu, Guowang

2015-07-01

The combination of the lipidome and the metabolome can provide much more information in plant metabolomics studies. A method for the simultaneous extraction of the lipidome and the metabolome of fresh tobacco leaves was developed. Method validation was performed on the basis of the optimal ratio of methanol to methyl tert-butyl ether to water (37:45:68) from the design of experiments. Good repeatability was obtained. We found that 92.2% and 91.6% of the peaks for the lipidome and the metabolome were within a relative standard deviation of 20%, accounting for 94.6% and 94.6% of the total abundance, respectively. The intraday and interday precisions were also satisfactory. A total of 230 metabolites, including 129 lipids, were identified. Significant differences were found in lipidomic and metabolomic profiles of fresh tobacco leaves in different geographical regions. Highly unsaturated galactolipids, phosphatidylethanolamines, predominant phosphatidylcholines, most of the polyphenols, amino acids, and polyamines had a higher content in Yunnan province, and low-unsaturation-degree galactolipids, triacylglycerols, glucosylceramides with trihydroxy long-chain bases, acylated sterol glucosides, and some organic acids were more abundant in Henan province. Correlation analysis between differential metabolites and climatic factors indicated the vital importance of temperature. The fatty acid unsaturation degree of galactolipids could be influenced by temperature. Accumulation of polyphenols and decreases in the ratios of stigmasterols to sitosterols and glucosylstigmasterols to glucosylsitosterols were also correlated with lower temperature in Yunnan province. Furthermore, lipids were more sensitive to climatic variations than other metabolites.

Establishment of Protocols for Global Metabolomics by LC-MS for Biomarker Discovery.

PubMed

Saigusa, Daisuke; Okamura, Yasunobu; Motoike, Ikuko N; Katoh, Yasutake; Kurosawa, Yasuhiro; Saijyo, Reina; Koshiba, Seizo; Yasuda, Jun; Motohashi, Hozumi; Sugawara, Junichi; Tanabe, Osamu; Kinoshita, Kengo; Yamamoto, Masayuki

2016-01-01

Metabolomics is a promising avenue for biomarker discovery. Although the quality of metabolomic analyses, especially global metabolomics (G-Met) using mass spectrometry (MS), largely depends on the instrumentation, potential bottlenecks still exist at several basic levels in the metabolomics workflow. Therefore, we established a precise protocol initially for the G-Met analyses of human blood plasma to overcome some these difficulties. In our protocol, samples are deproteinized in a 96-well plate using an automated liquid-handling system, and conducted either using a UHPLC-QTOF/MS system equipped with a reverse phase column or a LC-FTMS system equipped with a normal phase column. A normalization protocol of G-Met data was also developed to compensate for intra- and inter-batch differences, and the variations were significantly reduced along with our normalization, especially for the UHPLC-QTOF/MS data with a C18 reverse-phase column for positive ions. Secondly, we examined the changes in metabolomic profiles caused by the storage of EDTA-blood specimens to identify quality markers for the evaluation of the specimens' pre-analytical conditions. Forty quality markers, including lysophospholipids, dipeptides, fatty acids, succinic acid, amino acids, glucose, and uric acid were identified by G-Met for the evaluation of plasma sample quality and established the equation of calculating the quality score. We applied our quality markers to a small-scale study to evaluate the quality of clinical samples. The G-Met protocols and quality markers established here should prove useful for the discovery and development of biomarkers for a wider range of diseases.

From genomics to metabolomics, moving toward an integrated strategy for the discovery of fungal secondary metabolites.

PubMed

Hautbergue, T; Jamin, E L; Debrauwer, L; Puel, O; Oswald, I P

2018-02-21

Fungal secondary metabolites are defined by bioactive properties that ensure adaptation of the fungus to its environment. Although some of these natural products are promising sources of new lead compounds especially for the pharmaceutical industry, others pose risks to human and animal health. The identification of secondary metabolites is critical to assessing both the utility and risks of these compounds. Since fungi present biological specificities different from other microorganisms, this review covers the different strategies specifically used in fungal studies to perform this critical identification. Strategies focused on the direct detection of the secondary metabolites are firstly reported. Particularly, advances in high-throughput untargeted metabolomics have led to the generation of large datasets whose exploitation and interpretation generally require bioinformatics tools. Then, the genome-based methods used to study the entire fungal metabolic potential are reported. Transcriptomic and proteomic tools used in the discovery of fungal secondary metabolites are presented as links between genomic methods and metabolomic experiments. Finally, the influence of the culture environment on the synthesis of secondary metabolites by fungi is highlighted as a major factor to consider in research on fungal secondary metabolites. Through this review, we seek to emphasize that the discovery of natural products should integrate all of these valuable tools. Attention is also drawn to emerging technologies that will certainly revolutionize fungal research and to the use of computational tools that are necessary but whose results should be interpreted carefully.

Mass spectrometry-based plant metabolomics: Metabolite responses to abiotic stress.

PubMed

Jorge, Tiago F; Rodrigues, João A; Caldana, Camila; Schmidt, Romy; van Dongen, Joost T; Thomas-Oates, Jane; António, Carla

2016-09-01

Metabolomics is one omics approach that can be used to acquire comprehensive information on the composition of a metabolite pool to provide a functional screen of the cellular state. Studies of the plant metabolome include analysis of a wide range of chemical species with diverse physical properties, from ionic inorganic compounds to biochemically derived hydrophilic carbohydrates, organic and amino acids, and a range of hydrophobic lipid-related compounds. This complexitiy brings huge challenges to the analytical technologies employed in current plant metabolomics programs, and powerful analytical tools are required for the separation and characterization of this extremely high compound diversity present in biological sample matrices. The use of mass spectrometry (MS)-based analytical platforms to profile stress-responsive metabolites that allow some plants to adapt to adverse environmental conditions is fundamental in current plant biotechnology research programs for the understanding and development of stress-tolerant plants. In this review, we describe recent applications of metabolomics and emphasize its increasing application to study plant responses to environmental (stress-) factors, including drought, salt, low oxygen caused by waterlogging or flooding of the soil, temperature, light and oxidative stress (or a combination of them). Advances in understanding the global changes occurring in plant metabolism under specific abiotic stress conditions are fundamental to enhance plant fitness and increase stress tolerance. © 2015 Wiley Periodicals, Inc. Mass Spec Rev 35:620-649, 2016. © 2015 Wiley Periodicals, Inc.

Metabolic Mechanism for l-Leucine-Induced Metabolome To Eliminate Streptococcus iniae.

PubMed

Du, Chao-Chao; Yang, Man-Jun; Li, Min-Yi; Yang, Jun; Peng, Bo; Li, Hui; Peng, Xuan-Xian

2017-05-05

Crucial metabolites that modulate hosts' metabolome to eliminate bacterial pathogens have been documented, but the metabolic mechanisms are largely unknown. The present study explores the metabolic mechanism for l-leucine-induced metabolome to eliminate Streptococcus iniae in tilapia. GC-MS-based metabolomics was used to investigate the tilapia liver metabolic profile in the presence of exogenous l-leucine. Thirty-seven metabolites of differential abundance were determined, and 11 metabolic pathways were enriched. Pattern recognition analysis identified serine and proline as crucial metabolites, which are the two metabolites identified in survived tilapias during S. iniae infection, suggesting that the two metabolites play crucial roles in l-leucine-induced elimination of the pathogen by the host. Exogenous l-serine reduces the mortality of tilapias infected by S. iniae, providing a robust proof supporting the conclusion. Furthermore, exogenous l-serine elevates expression of genes IL-1β and IL-8 in tilapia spleen, but not TNFα, CXCR4 and Mx, suggesting that the metabolite promotes a phagocytosis role of macrophages, which is consistent with the finding that l-leucine promotes macrophages to kill both Gram-positive and Gram-negative bacterial pathogens. Therefore, the ability of phagocytosis enhanced by exogenous l-leucine is partly attributed to elevation of l-serine. These results demonstrate a metabolic mechanism by which exogenous l-leucine modulates tilapias' metabolome to enhance innate immunity and eliminate pathogens.

Comparative Metabolome Profile between Tobacco and Soybean Grown under Water-Stressed Conditions.

PubMed

Rabara, Roel C; Tripathi, Prateek; Rushton, Paul J

2017-01-01

Understanding how plants respond to water deficit is important in order to develop crops tolerant to drought. In this study, we compare two large metabolomics datasets where we employed a nontargeted metabolomics approach to elucidate metabolic pathways perturbed by progressive dehydration in tobacco and soybean plants. The two datasets were created using the same strategy to create water deficit conditions and an identical metabolomics pipeline. Comparisons between the two datasets therefore reveal common responses between the two species, responses specific to one of the species, responses that occur in both root and leaf tissues, and responses that are specific to one tissue. Stomatal closure is the immediate response of the plant and this did not coincide with accumulation of abscisic acid. A total of 116 and 140 metabolites were observed in tobacco leaves and roots, respectively, while 241 and 207 were observed in soybean leaves and roots, respectively. Accumulation of metabolites is significantly correlated with the extent of dehydration in both species. Among the metabolites that show increases that are restricted to just one plant, 4-hydroxy-2-oxoglutaric acid (KHG) in tobacco roots and coumestrol in soybean roots show the highest tissue-specific accumulation. The comparisons of these two large nontargeted metabolomics datasets provide novel information and suggest that KHG will be a useful marker for drought stress for some members of Solanaceae and coumestrol for some legume species.

Evaluation of metabolites extraction strategies for identifying different brain regions and their relationship with alcohol preference and gender difference using NMR metabolomics.

PubMed

Wang, Jie; Zeng, Hao-Long; Du, Hongying; Liu, Zeyuan; Cheng, Ji; Liu, Taotao; Hu, Ting; Kamal, Ghulam Mustafa; Li, Xihai; Liu, Huili; Xu, Fuqiang

2018-03-01

Metabolomics generate a profile of small molecules from cellular/tissue metabolism, which could directly reflect the mechanisms of complex networks of biochemical reactions. Traditional metabolomics methods, such as OPLS-DA, PLS-DA are mainly used for binary class discrimination. Multiple groups are always involved in the biological system, especially for brain research. Multiple brain regions are involved in the neuronal study of brain metabolic dysfunctions such as alcoholism, Alzheimer's disease, etc. In the current study, 10 different brain regions were utilized for comparative studies between alcohol preferring and non-preferring rats, male and female rats respectively. As many classes are involved (ten different regions and four types of animals), traditional metabolomics methods are no longer efficient for showing differentiation. Here, a novel strategy based on the decision tree algorithm was employed for successfully constructing different classification models to screen out the major characteristics of ten brain regions at the same time. Subsequently, this method was also utilized to select the major effective brain regions related to alcohol preference and gender difference. Compared with the traditional multivariate statistical methods, the decision tree could construct acceptable and understandable classification models for multi-class data analysis. Therefore, the current technology could also be applied to other general metabolomics studies involving multi class data. Copyright © 2017 Elsevier B.V. All rights reserved.

Water-soluble vitamin homeostasis in fasting northern elephant seals (Mirounga angustirostris) measured by metabolomics analysis and standard methods.

PubMed

Boaz, Segal M; Champagne, Cory D; Fowler, Melinda A; Houser, Dorian H; Crocker, Daniel E

2012-02-01

Despite the importance of water-soluble vitamins to metabolism, there is limited knowledge of their serum availability in fasting wildlife. We evaluated changes in water-soluble vitamins in northern elephant seals, a species with an exceptional ability to withstand nutrient deprivation. We used a metabolomics approach to measure vitamins and associated metabolites under extended natural fasts for up to 7 weeks in free-ranging lactating or developing seals. Water-soluble vitamins were not detected with this metabolomics platform, but could be measured with standard assays. Concentrations of measured vitamins varied independently, but all were maintained at detectable levels over extended fasts, suggesting that defense of vitamin levels is a component of fasting adaptation in the seals. Metabolomics was not ideal for generating complete vitamin profiles in this species, but gave novel insights into vitamin metabolism by detecting key related metabolites. For example, niacin level reductions in lactating females were associated with significant reductions in precursors suggesting downregulation of the niacin synthetic pathway. The ability to detect individual vitamins using metabolomics may be impacted by the large number of novel compounds detected. Modifications to the analysis platforms and compound detection algorithms used in this study may be required for improving water-soluble vitamin detection in this and other novel wildlife systems. Copyright © 2011 Elsevier Inc. All rights reserved.

Systems-Level Annotation of a Metabolomics Data Set Reduces 25 000 Features to Fewer than 1000 Unique Metabolites.

PubMed

Mahieu, Nathaniel G; Patti, Gary J

2017-10-03

When using liquid chromatography/mass spectrometry (LC/MS) to perform untargeted metabolomics, it is now routine to detect tens of thousands of features from biological samples. Poor understanding of the data, however, has complicated interpretation and masked the number of unique metabolites actually being measured in an experiment. Here we place an upper bound on the number of unique metabolites detected in Escherichia coli samples analyzed with one untargeted metabolomics method. We first group multiple features arising from the same analyte, which we call "degenerate features", using a context-driven annotation approach. Surprisingly, this analysis revealed thousands of previously unreported degeneracies that reduced the number of unique analytes to ∼2961. We then applied an orthogonal approach to remove nonbiological features from the data using the 13 C-based credentialing technology. This further reduced the number of unique analytes to less than 1000. Our 90% reduction in data is 5-fold greater than previously published studies. On the basis of the results, we propose an alternative approach to untargeted metabolomics that relies on thoroughly annotated reference data sets. To this end, we introduce the creDBle database ( http://creDBle.wustl.edu ), which contains accurate mass, retention time, and MS/MS fragmentation data as well as annotations of all credentialed features.

Metabolomics of dates (Phoenix dactylifera) reveals a highly dynamic ripening process accounting for major variation in fruit composition.

PubMed

Diboun, Ilhame; Mathew, Sweety; Al-Rayyashi, Maryam; Elrayess, Mohamed; Torres, Maria; Halama, Anna; Méret, Michaël; Mohney, Robert P; Karoly, Edward D; Malek, Joel; Suhre, Karsten

2015-12-16

Dates are tropical fruits with appreciable nutritional value. Previous attempts at global metabolic characterization of the date metabolome were constrained by small sample size and limited geographical sampling. In this study, two independent large cohorts of mature dates exhibiting substantial diversity in origin, varieties and fruit processing conditions were measured by metabolomics techniques in order to identify major determinants of the fruit metabolome. Multivariate analysis revealed a first principal component (PC1) significantly associated with the dates' countries of production. The availability of a smaller dataset featuring immature dates from different development stages served to build a model of the ripening process in dates, which helped reveal a strong ripening signature in PC1. Analysis revealed enrichment in the dry type of dates amongst fruits with early ripening profiles at one end of PC1 as oppose to an overrepresentation of the soft type of dates with late ripening profiles at the other end of PC1. Dry dates are typical to the North African region whilst soft dates are more popular in the Gulf region, which partly explains the observed association between PC1 and geography. Analysis of the loading values, expressing metabolite correlation levels with PC1, revealed enrichment patterns of a comprehensive range of metabolite classes along PC1. Three distinct metabolic phases corresponding to known stages of date ripening were observed: An early phase enriched in regulatory hormones, amines and polyamines, energy production, tannins, sucrose and anti-oxidant activity, a second phase with on-going phenylpropanoid secondary metabolism, gene expression and phospholipid metabolism and a late phase with marked sugar dehydration activity and degradation reactions leading to increased volatile synthesis. These data indicate the importance of date ripening as a main driver of variation in the date metabolome responsible for their diverse nutritional and economical values. The biochemistry of the ripening process in dates is consistent with other fruits but natural dryness may prevent degenerative senescence in dates following ripening. Based on the finding that mature dates present varying extents of ripening, our survey of the date metabolome essentially revealed snapshots of interchanging metabolic states during ripening empowering an in-depth characterization of underlying biology.

Changes in metabolic profiles during acute kidney injury and recovery following ischemia/reperfusion.

PubMed

Wei, Qingqing; Xiao, Xiao; Fogle, Paul; Dong, Zheng

2014-01-01

Changes of metabolism have been implicated in renal ischemia/reperfusion injury (IRI). However, a global analysis of the metabolic changes in renal IRI is lacking and the association of the changes with ischemic kidney injury and subsequent recovery are unclear. In this study, mice were subjected to 25 minutes of bilateral renal IRI followed by 2 hours to 7 days of reperfusion. Kidney injury and subsequent recovery was verified by serum creatinine and blood urea nitrogen measurements. The metabolome of plasma, kidney cortex, and medulla were profiled by the newly developed global metabolomics analysis. Renal IRI induced overall changes of the metabolome in plasma and kidney tissues. The changes started in renal cortex, followed by medulla and plasma. In addition, we identified specific metabolites that may contribute to early renal injury response, perturbed energy metabolism, impaired purine metabolism, impacted osmotic regulation and the induction of inflammation. Some metabolites, such as 3-indoxyl sulfate, were induced at the earliest time point of renal IRI, suggesting the potential of being used as diagnostic biomarkers. There was a notable switch of energy source from glucose to lipids, implicating the importance of appropriate nutrition supply during treatment. In addition, we detected the depressed polyols for osmotic regulation which may contribute to the loss of kidney function. Several pathways involved in inflammation regulation were also induced. Finally, there was a late induction of prostaglandins, suggesting their possible involvement in kidney recovery. In conclusion, this study demonstrates significant changes of metabolome kidney tissues and plasma in renal IRI. The changes in specific metabolites are associated with and may contribute to early injury, shift of energy source, inflammation, and late phase kidney recovery.

Changes in Metabolic Profiles during Acute Kidney Injury and Recovery following Ischemia/Reperfusion

PubMed Central

Wei, Qingqing; Xiao, Xiao; Fogle, Paul; Dong, Zheng

2014-01-01

Changes of metabolism have been implicated in renal ischemia/reperfusion injury (IRI). However, a global analysis of the metabolic changes in renal IRI is lacking and the association of the changes with ischemic kidney injury and subsequent recovery are unclear. In this study, mice were subjected to 25 minutes of bilateral renal IRI followed by 2 hours to 7 days of reperfusion. Kidney injury and subsequent recovery was verified by serum creatinine and blood urea nitrogen measurements. The metabolome of plasma, kidney cortex, and medulla were profiled by the newly developed global metabolomics analysis. Renal IRI induced overall changes of the metabolome in plasma and kidney tissues. The changes started in renal cortex, followed by medulla and plasma. In addition, we identified specific metabolites that may contribute to early renal injury response, perturbed energy metabolism, impaired purine metabolism, impacted osmotic regulation and the induction of inflammation. Some metabolites, such as 3-indoxyl sulfate, were induced at the earliest time point of renal IRI, suggesting the potential of being used as diagnostic biomarkers. There was a notable switch of energy source from glucose to lipids, implicating the importance of appropriate nutrition supply during treatment. In addition, we detected the depressed polyols for osmotic regulation which may contribute to the loss of kidney function. Several pathways involved in inflammation regulation were also induced. Finally, there was a late induction of prostaglandins, suggesting their possible involvement in kidney recovery. In conclusion, this study demonstrates significant changes of metabolome kidney tissues and plasma in renal IRI. The changes in specific metabolites are associated with and may contribute to early injury, shift of energy source, inflammation, and late phase kidney recovery. PMID:25191961

'Systems toxicology' approach identifies coordinated metabolic responses to copper in a terrestrial non-model invertebrate, the earthworm Lumbricus rubellus.

PubMed

Bundy, Jacob G; Sidhu, Jasmin K; Rana, Faisal; Spurgeon, David J; Svendsen, Claus; Wren, Jodie F; Stürzenbaum, Stephen R; Morgan, A John; Kille, Peter

2008-06-03

New methods are needed for research into non-model organisms, to monitor the effects of toxic disruption at both the molecular and functional organism level. We exposed earthworms (Lumbricus rubellus Hoffmeister) to sub-lethal levels of copper (10-480 mg/kg soil) for 70 days as a real-world situation, and monitored both molecular (cDNA transcript microarrays and nuclear magnetic resonance-based metabolic profiling: metabolomics) and ecological/functional endpoints (reproduction rate and weight change, which have direct relevance to population-level impacts). Both of the molecular endpoints, metabolomics and transcriptomics, were highly sensitive, with clear copper-induced differences even at levels below those that caused a reduction in reproductive parameters. The microarray and metabolomic data provided evidence that the copper exposure led to a disruption of energy metabolism: transcripts of enzymes from oxidative phosphorylation were significantly over-represented, and increases in transcripts of carbohydrate metabolising enzymes (maltase-glucoamylase, mannosidase) had corresponding decreases in small-molecule metabolites (glucose, mannose). Treating both enzymes and metabolites as functional cohorts led to clear inferences about changes in energetic metabolism (carbohydrate use and oxidative phosphorylation), which would not have been possible by taking a 'biomarker' approach to data analysis. Multiple post-genomic techniques can be combined to provide mechanistic information about the toxic effects of chemical contaminants, even for non-model organisms with few additional mechanistic toxicological data. With 70-day no-observed-effect and lowest-observed-effect concentrations (NOEC and LOEC) of 10 and 40 mg kg-1 for metabolomic and microarray profiles, copper is shown to interfere with energy metabolism in an important soil organism at an ecologically and functionally relevant level.

The impact of ambient air pollution on the human blood metabolome.

PubMed

Vlaanderen, J J; Janssen, N A; Hoek, G; Keski-Rahkonen, P; Barupal, D K; Cassee, F R; Gosens, I; Strak, M; Steenhof, M; Lan, Q; Brunekreef, B; Scalbert, A; Vermeulen, R C H

2017-07-01

Biological perturbations caused by air pollution might be reflected in the compounds present in blood originating from air pollutants and endogenous metabolites influenced by air pollution (defined here as part of the blood metabolome). We aimed to assess the perturbation of the blood metabolome in response to short term exposure to air pollution. We exposed 31 healthy volunteers to ambient air pollution for 5h. We measured exposure to particulate matter, particle number concentrations, absorbance, elemental/organic carbon, trace metals, secondary inorganic components, endotoxin content, gaseous pollutants, and particulate matter oxidative potential. We collected blood from the participants 2h before and 2 and 18h after exposure. We employed untargeted metabolite profiling to monitor 3873 metabolic features in 493 blood samples from these volunteers. We assessed lung function using spirometry and six acute phase proteins in peripheral blood. We assessed the association of the metabolic features with the measured air pollutants and with health markers that we previously observed to be associated with air pollution in this study. We observed 89 robust associations between air pollutants and metabolic features two hours after exposure and 118 robust associations 18h after exposure. Some of the metabolic features that were associated with air pollutants were also associated with acute health effects, especially changes in forced expiratory volume in 1s. We successfully identified tyrosine, guanosine, and hypoxanthine among the associated features. Bioinformatics approach Mummichog predicted enriched pathway activity in eight pathways, among which tyrosine metabolism. This study demonstrates for the first time the application of untargeted metabolite profiling to assess the impact of air pollution on the blood metabolome. Copyright © 2017 Elsevier Inc. All rights reserved.

Metabolome of Vanilla planifolia (Orchidaceae) and related species under Cymbidium mosaic virus (CymMV) infection.

PubMed

Palama, Tony Lionel; Grisoni, Michel; Fock-Bastide, Isabelle; Jade, Katia; Bartet, Laetitia; Choi, Young Hae; Verpoorte, Robert; Kodja, Hippolyte

2012-11-01

The genus Vanilla which belongs to the Orchidaceae family comprises more than 110 species of which two are commercially cultivated (Vanilla planifolia and Vanilla xtahitensis). The cured pods of these species are the source of natural vanilla flavor. In intensive cultivation systems the vines are threatened by viruses such as Cymbidium mosaic virus (CymMV). In order to investigate the effect of CymMV on the growth and metabolome of vanilla plants, four accessions grown in intensive cultivation systems under shadehouse, CR01 (V. planifolia), CR17 (V. xtahitensis), CR03 (V. planifolia × V. xtahitensis) and CR18 (Vanilla pompona), were challenged with an isolate of CymMV. CymMV infected plants of CR01, CR03 and CR17 had a reduced growth compared to healthy plants, while there was no significant difference in the growth of CR18 vines. Interestingly, CR18 had qualitatively more phenolic compounds in leaves and a virus titre that diminished over time. No differences in the metabolomic profiles of the shadehouse samples obtained by nuclear magnetic resonance (NMR) were observed between the virus infected vs. healthy plants. However, using in- vitro V. planifolia plants, the metabolomic profiles were affected by virus infection. Under these controlled conditions the levels of amino acids and sugars present in the leaves were increased in CymMV infected plants, compared to uninfected ones, whereas the levels of phenolic compounds and malic acid were decreased. The metabolism, growth and viral status of V. pompona accession CR18 contrasted from that of the other species suggesting the existence of partial resistance to CymMV in the vanilla germplasm. Copyright © 2012 Elsevier Masson SAS. All rights reserved.

An acetyl-L-carnitine switch on mitochondrial dysfunction and rescue in the metabolomics study on aluminum oxide nanoparticles.

PubMed

Li, Xiaobo; Zhang, Chengcheng; Zhang, Xin; Wang, Shizhi; Meng, Qingtao; Wu, Shenshen; Yang, Hongbao; Xia, Yankai; Chen, Rui

2016-01-16

Due to the wide application of engineered aluminum oxide nanoparticles and increased aluminum containing particulate matter suspending in air, exposure of human to nano-scale aluminum oxide nanoparticles (Al2O3 NPs) is becoming inevitable. In the present study, RNA microarray coupled with metabolomics analysis were used to uncover mechanisms underlying cellular responses to Al2O3 NPs and imply the potential rescue. We found that Al2O3 NPs significantly triggered down-regulation of mitochondria-related genes located in complex I, IV and V, which were involved in oxidative phosphorylation and neural degeneration pathways, in human bronchial epithelial (HBE) cells. Subsequent cell- and animal- based assays confirmed that Al2O3 NPs caused mitochondria-dependent apoptosis and oxidative stress either in vitro or in vivo, which were consistent with the trends of gene regulation. To rescue the Al2O3 NPs induced mitochondria dysfunction, disruption of small molecular metabolites of HBE were profiled using metabolomics analysis, which facilitates identification of potential antagonizer or supplement against nanoparticle-involved damages. Supplementation of an antioxidant, acetyl-L-carnitine, completely or partially restored the Al2O3 NPs modulated gene expression levels in mitochondrial complex I, IV and V. It further reduced apoptosis and oxidative damages in both Al2O3 NPs treated HBE cells and animal lung tissues. Thus, our results demonstrate the potential mechanism of respiratory system damages induced by Al2O3 NPs. Meanwhile, based on the metabolomics profiling, application of acetyl-L-carnitine is suggested to ameliorate mitochondria dysfunction associated with Al2O3 NPs.

Structure elucidation of metabolite x17299 by interpretation of mass spectrometric data.

PubMed

Zhang, Qibo; Ford, Lisa A; Evans, Anne M; Toal, Douglas R

2017-01-01

A major bottleneck in metabolomic studies is metabolite identification from accurate mass spectrometric data. Metabolite x17299 was identified in plasma as an unknown in a metabolomic study using a compound-centric approach where the associated ion features of the compound were used to determine the true molecular mass. The aim of this work is to elucidate the chemical structure of x17299, a new compound by de novo interpretation of mass spectrometric data. An Orbitrap Elite mass spectrometer was used for acquisition of mass spectra up to MS 4 at high resolution. Synthetic standards of N,N,N -trimethyl-l-alanyl-l-proline betaine (l,l-TMAP), a diastereomer, and an enantiomer were chemically prepared. The planar structure of x17299 was successfully proposed by de novo mechanistic interpretation of mass spectrometric data without any laborious purification and nuclear magnetic resonance spectroscopic analysis. The proposed structure was verified by deuterium exchanged mass spectrometric analysis and confirmed by comparison to a synthetic standard. Relative configuration of x17299 was determined by direct chromatographic comparison to a pair of synthetic diastereomers. Absolute configuration was assigned after derivatization of x17299 with a chiral auxiliary group followed by its chromatographic comparison to a pair of synthetic standards. The chemical structure of metabolite x17299 was determined to be l,l-TMAP.

A Generic Multiple Reaction Monitoring Based Approach for Plant Flavonoids Profiling Using a Triple Quadrupole Linear Ion Trap Mass Spectrometry

NASA Astrophysics Data System (ADS)

Yan, Zhixiang; Lin, Ge; Ye, Yang; Wang, Yitao; Yan, Ru

2014-06-01

Flavonoids are one of the largest classes of plant secondary metabolites serving a variety of functions in plants and associating with a number of health benefits for humans. Typically, they are co-identified with many other secondary metabolites using untargeted metabolomics. The limited data quality of untargeted workflow calls for a shift from the breadth-first to the depth-first screening strategy when a specific biosynthetic pathway is focused on. Here we introduce a generic multiple reaction monitoring (MRM)-based approach for flavonoids profiling in plants using a hybrid triple quadrupole linear ion trap (QTrap) mass spectrometer. The approach includes four steps: (1) preliminary profiling of major aglycones by multiple ion monitoring triggered enhanced product ion scan (MIM-EPI); (2) glycones profiling by precursor ion triggered EPI scan (PI-EPI) of major aglycones; (3) comprehensive aglycones profiling by combining MIM-EPI and neutral loss triggered EPI scan (NL-EPI) of major glycone; (4) in-depth flavonoids profiling by MRM-EPI with elaborated MRM transitions. Particularly, incorporation of the NH3 loss and sugar elimination proved to be very informative and confirmative for flavonoids screening. This approach was applied for profiling flavonoids in Astragali radix ( Huangqi), a famous herb widely used for medicinal and nutritional purposes in China. In total, 421 flavonoids were tentatively characterized, among which less than 40 have been previously reported in this medicinal plant. This MRM-based approach provides versatility and sensitivity that required for flavonoids profiling in plants and serves as a useful tool for plant metabolomics.

Evaluation of the Nutritional Quality of Chinese Kale (Brassica alboglabra Bailey) Using UHPLC-Quadrupole-Orbitrap MS/MS-Based Metabolomics.

PubMed

Wang, Ya-Qin; Hu, Li-Ping; Liu, Guang-Min; Zhang, De-Shuang; He, Hong-Ju

2017-07-27

Chinese kale ( Brassica alboglabra Bailey) is a widely consumed vegetable which is rich in antioxidants and anticarcinogenic compounds. Herein, we used an untargeted ultra-high-performance liquid chromatography (UHPLC)-Quadrupole-Orbitrap MS/MS-based metabolomics strategy to study the nutrient profiles of Chinese kale. Seven Chinese kale cultivars and three different edible parts were evaluated, and amino acids, sugars, organic acids, glucosinolates and phenolic compounds were analysed simultaneously. We found that two cultivars, a purple-stem cultivar W1 and a yellow-flower cultivar Y1, had more health-promoting compounds than others. The multivariate statistical analysis results showed that gluconapin was the most important contributor for discriminating both cultivars and edible parts. The purple-stem cultivar W1 had higher levels of some phenolic acids and flavonoids than the green stem cultivars. Compared to stems and leaves, the inflorescences contained more amino acids, glucosinolates and most of the phenolic acids. Meanwhile, the stems had the least amounts of phenolic compounds among the organs tested. Metabolomics is a powerful approach for the comprehensive understanding of vegetable nutritional quality. The results provide the basis for future metabolomics-guided breeding and nutritional quality improvement.

The Chemistry of Plant–Microbe Interactions in the Rhizosphere and the Potential for Metabolomics to Reveal Signaling Related to Defense Priming and Induced Systemic Resistance

PubMed Central

Mhlongo, Msizi I.; Piater, Lizelle A.; Madala, Ntakadzeni E.; Labuschagne, Nico; Dubery, Ian A.

2018-01-01

Plant roots communicate with microbes in a sophisticated manner through chemical communication within the rhizosphere, thereby leading to biofilm formation of beneficial microbes and, in the case of plant growth-promoting rhizomicrobes/-bacteria (PGPR), resulting in priming of defense, or induced resistance in the plant host. The knowledge of plant–plant and plant–microbe interactions have been greatly extended over recent years; however, the chemical communication leading to priming is far from being well understood. Furthermore, linkage between below- and above-ground plant physiological processes adds to the complexity. In metabolomics studies, the main aim is to profile and annotate all exo- and endo-metabolites in a biological system that drive and participate in physiological processes. Recent advances in this field has enabled researchers to analyze 100s of compounds in one sample over a short time period. Here, from a metabolomics viewpoint, we review the interactions within the rhizosphere and subsequent above-ground ‘signalomics’, and emphasize the contributions that mass spectrometric-based metabolomic approaches can bring to the study of plant-beneficial – and priming events. PMID:29479360

Metabolic Profiling as a Screening Tool for Cytotoxic Compounds: Identification of 3-Alkyl Pyridine Alkaloids from Sponges Collected at a Shallow Water Hydrothermal Vent Site North of Iceland

PubMed Central

Einarsdottir, Eydis; Magnusdottir, Manuela; Astarita, Giuseppe; Köck, Matthias; Ögmundsdottir, Helga M.; Thorsteinsdottir, Margret; Rapp, Hans Tore; Omarsdottir, Sesselja; Paglia, Giuseppe

2017-01-01

Twenty-eight sponge specimens were collected at a shallow water hydrothermal vent site north of Iceland. Extracts were prepared and tested in vitro for cytotoxic activity, and eight of them were shown to be cytotoxic. A mass spectrometry (MS)-based metabolomics approach was used to determine the chemical composition of the extracts. This analysis highlighted clear differences in the metabolomes of three sponge specimens, and all of them were identified as Haliclona (Rhizoniera) rosea (Bowerbank, 1866). Therefore, these specimens were selected for further investigation. Haliclona rosea metabolomes contained a class of potential key compounds, the 3-alkyl pyridine alkaloids (3-APA) responsible for the cytotoxic activity of the fractions. Several 3-APA compounds were tentatively identified including haliclamines, cyclostellettamines, viscosalines and viscosamines. Among these compounds, cyclostellettamine P was tentatively identified for the first time by using ion mobility MS in time-aligned parallel (TAP) fragmentation mode. In this work, we show the potential of applying metabolomics strategies and in particular the utility of coupling ion mobility with MS for the molecular characterization of sponge specimens. PMID:28241423

Metabolomics profiles delineate uridine deficiency contributes to mitochondria-mediated apoptosis induced by celastrol in human acute promyelocytic leukemia cells

PubMed Central

Li, Lei; Huan, Fei; Li, Aiping; Liu, Yanqing; Xia, Yankai; Duan, Jin-ao; Ma, Shiping

2016-01-01

Celastrol, extracted from “Thunder of God Vine”, is a promising anti-cancer natural product. However, its effect on acute promyelocytic leukemia (APL) and underlying molecular mechanism are poorly understood. The purpose of this study was to explore its effect on APL and underlying mechanism based on metabolomics. Firstly, multiple assays indicated that celastrol could induce apoptosis of APL cells via p53-activated mitochondrial pathway. Secondly, unbiased metabolomics revealed that uridine was the most notable changed metabolite. Further study verified that uridine could reverse the apoptosis induced by celastrol. The decreased uridine was caused by suppressing the expression of gene encoding Dihydroorotate dehydrogenase, whose inhibitor could also induce apoptosis of APL cells. At last, mouse model confirmed that celastrol inhibited tumor growth through enhanced apoptosis. Celastrol could also decrease uridine and DHODH protein level in tumor tissues. Our in vivo study also indicated that celastrol had no systemic toxicity at pharmacological dose (2 mg/kg, i.p., 21 days). Altogether, our metabolomics study firstly reveals that uridine deficiency contributes to mitochondrial apoptosis induced by celastrol in APL cells. Celastrol shows great potential for the treatment of APL. PMID:27374097

Metabolomic effects of xylitol and fluoride on plaque biofilm in vivo.

PubMed

Takahashi, N; Washio, J

2011-12-01

Dental caries is initiated by demineralization of the tooth surface through acid production from sugar by plaque biofilm. Fluoride and xylitol have been used worldwide as caries-preventive reagents, based on in vitro-proven inhibitory mechanisms on bacterial acid production. We attempted to confirm the inhibitory mechanisms of fluoride and xylitol in vivo by performing metabolome analysis on the central carbon metabolism in supragingival plaque using the combination of capillary electrophoresis and a time-of-flight mass spectrometer. Fluoride (225 and 900 ppm F(-)) inhibited lactate production from 10% glucose by 34% and 46%, respectively, along with the increase in 3-phosphoglycerate and the decrease in phosphoenolpyruvate in the EMP pathway in supragingival plaque. These results confirmed that fluoride inhibited bacterial enolase in the EMP pathway and subsequently repressed acid production in vivo. In contrast, 10% xylitol had no effect on acid production and the metabolome profile in supragingival plaque, although xylitol 5-phosphate was produced. These results suggest that xylitol is not an inhibitor of plaque acid production but rather a non-fermentative sugar alcohol. Metabolome analyses of plaque biofilm can be applied for monitoring the efficacy of dietary components and medicines for plaque biofilm, leading to the development of effective plaque control.

Current Advances in the Metabolomics Study on Lotus Seeds.

PubMed

Zhu, Mingzhi; Liu, Ting; Guo, Mingquan

2016-01-01

Lotus (Nelumbo nucifera), which is distributed widely throughout Asia, Australia and North America, is an aquatic perennial that has been cultivated for over 2,000 years. It is very stimulating that almost all parts of lotus have been consumed as vegetable as well as food, especially the seeds. Except for the nutritive values of lotus, there has been increasing interest in its potential as functional food due to its rich secondary metabolites, such as flavonoids and alkaloids. Not only have these metabolites greatly contributed to the biological process of lotus seeds, but also have been reported to possess multiple health-promoting effects, including antioxidant, anti-amnesic, anti-inflammatory, and anti-tumor activities. Thus, comprehensive metabolomic profiling of these metabolites is of key importance to help understand their biological activities, and other chemical biology features. In this context, this review will provide an update on the current technological platforms, and workflow associated with metabolomic studies on lotus seeds, as well as insights into the application of metabolomics for the improvement of food safety and quality, assisting breeding, and promotion of the study of metabolism and pharmacokinetics of lotus seeds; meanwhile it will also help explore new perspectives and outline future challenges in this fast-growing research subject.

NMR-based metabolomics approach to study the chronic toxicity of crude ricin from castor bean kernels on rats.

PubMed

Guo, Pingping; Wang, Junsong; Dong, Ge; Wei, Dandan; Li, Minghui; Yang, Minghua; Kong, Lingyi

2014-07-29

Ricin, a large, water soluble toxic glycoprotein, is distributed majorly in the kernels of castor beans (the seeds of Ricinus communis L.) and has been used in traditional Chinese medicine (TCM) or other folk remedies throughout the world. The toxicity of crude ricin (CR) from castor bean kernels was investigated for the first time using an NMR-based metabolomic approach complemented with histopathological inspection and clinical chemistry. The chronic administration of CR could cause kidney and lung impairment, spleen and thymus dysfunction and diminished nutrient intake in rats. An orthogonal signal correction partial least-squares discriminant analysis (OSC-PLSDA) of metabolomic profiles of rat biofluids highlighted a number of metabolic disturbances induced by CR. Long-term CR treatment produced perturbations on energy metabolism, nitrogen metabolism, amino acid metabolism and kynurenine pathway, and evoked oxidative stress. These findings could explain well the CR induced nephrotoxicity and pulmonary toxicity, and provided several potential biomarkers for diagnostics of these toxicities. Such a (1)H NMR based metabolomics approach showed its ability to give a systematic and holistic view of the response of an organism to drugs and is suitable for dynamic studies on the toxicological effects of TCM.

Metabolite profiling of fish skin mucus: a novel approach for minimally-invasive environmental exposure monitoring and surveillance.

PubMed

Ekman, D R; Skelton, D M; Davis, J M; Villeneuve, D L; Cavallin, J E; Schroeder, A; Jensen, K M; Ankley, G T; Collette, T W

2015-03-03

The application of 'omics tools to biologically based monitoring and surveillance of aquatic environments shows considerable promise for complementing chemical monitoring in ecological risk assessments. However, few of the current approaches offer the ability to sample ecologically relevant species (e.g., fish) in a way that produces minimal impact on the health of the organism(s) under study. In the current study we employ liquid chromatography tandem mass spectrometry (LC-MS/MS) to assess the potential for skin mucus-based metabolomics for minimally invasive sampling of the fathead minnow (FHM; Pimephales promelas). Using this approach we were able to detect 204 distinct metabolites in the FHM skin mucus metabolome representing a large number of metabolite classes. An analysis of the sex specificity of the skin mucus metabolome showed it to be highly sexually dimorphic with 72 of the detected metabolites showing a statistically significant bias with regard to sex. Finally, in a proof-of-concept fashion we report on the use of skin mucus-based metabolomics to assess exposures in male and female fathead minnows to an environmentally relevant concentration of bisphenol A, a nearly ubiquitous environmental contaminant and an established endocrine active chemical.

MaizeCyc: Metabolic networks in maize

USDA-ARS?s Scientific Manuscript database

MaizeCyc is a catalog of known and predicted metabolic and transport pathways that enables plant researchers to graphically represent the metabolome of maize (Zea mays), thereby supporting integrated systems-biology analysis. Supported analyses include molecular and genetic/phenotypic profiling (e.g...

Profile-Based LC-MS Data Alignment—A Bayesian Approach

PubMed Central

Tsai, Tsung-Heng; Tadesse, Mahlet G.; Wang, Yue; Ressom, Habtom W.

2014-01-01

A Bayesian alignment model (BAM) is proposed for alignment of liquid chromatography-mass spectrometry (LC-MS) data. BAM belongs to the category of profile-based approaches, which are composed of two major components: a prototype function and a set of mapping functions. Appropriate estimation of these functions is crucial for good alignment results. BAM uses Markov chain Monte Carlo (MCMC) methods to draw inference on the model parameters and improves on existing MCMC-based alignment methods through 1) the implementation of an efficient MCMC sampler and 2) an adaptive selection of knots. A block Metropolis-Hastings algorithm that mitigates the problem of the MCMC sampler getting stuck at local modes of the posterior distribution is used for the update of the mapping function coefficients. In addition, a stochastic search variable selection (SSVS) methodology is used to determine the number and positions of knots. We applied BAM to a simulated data set, an LC-MS proteomic data set, and two LC-MS metabolomic data sets, and compared its performance with the Bayesian hierarchical curve registration (BHCR) model, the dynamic time-warping (DTW) model, and the continuous profile model (CPM). The advantage of applying appropriate profile-based retention time correction prior to performing a feature-based approach is also demonstrated through the metabolomic data sets. PMID:23929872

EU Framework 6 Project: Predictive Toxicology (PredTox)-overview and outcome

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

Suter, Laura, E-mail: Laura.suter-dick@roche.com; Schroeder, Susanne; Meyer, Kirstin

2011-04-15

In this publication, we report the outcome of the integrated EU Framework 6 Project: Predictive Toxicology (PredTox), including methodological aspects and overall conclusions. Specific details including data analysis and interpretation are reported in separate articles in this issue. The project, partly funded by the EU, was carried out by a consortium of 15 pharmaceutical companies, 2 SMEs, and 3 universities. The effects of 16 test compounds were characterized using conventional toxicological parameters and 'omics' technologies. The three major observed toxicities, liver hypertrophy, bile duct necrosis and/or cholestasis, and kidney proximal tubular damage were analyzed in detail. The combined approach ofmore » 'omics' and conventional toxicology proved a useful tool for mechanistic investigations and the identification of putative biomarkers. In our hands and in combination with histopathological assessment, target organ transcriptomics was the most prolific approach for the generation of mechanistic hypotheses. Proteomics approaches were relatively time-consuming and required careful standardization. NMR-based metabolomics detected metabolite changes accompanying histopathological findings, providing limited additional mechanistic information. Conversely, targeted metabolite profiling with LC/GC-MS was very useful for the investigation of bile duct necrosis/cholestasis. In general, both proteomics and metabolomics were supportive of other findings. Thus, the outcome of this program indicates that 'omics' technologies can help toxicologists to make better informed decisions during exploratory toxicological studies. The data support that hypothesis on mode of action and discovery of putative biomarkers are tangible outcomes of integrated 'omics' analysis. Qualification of biomarkers remains challenging, in particular in terms of identification, mechanistic anchoring, appropriate specificity, and sensitivity.« less

Automated LC-HRMS(/MS) Approach for the Annotation of Fragment Ions Derived from Stable Isotope Labeling-Assisted Untargeted Metabolomics

PubMed Central

2014-01-01

Structure elucidation of biological compounds is still a major bottleneck of untargeted LC-HRMS approaches in metabolomics research. The aim of the present study was to combine stable isotope labeling and tandem mass spectrometry for the automated interpretation of the elemental composition of fragment ions and thereby facilitate the structural characterization of metabolites. The software tool FragExtract was developed and evaluated with LC-HRMS/MS spectra of both native 12C- and uniformly 13C (U-13C)-labeled analytical standards of 10 fungal substances in pure solvent and spiked into fungal culture filtrate of Fusarium graminearum respectively. Furthermore, the developed approach is exemplified with nine unknown biochemical compounds contained in F. graminearum samples derived from an untargeted metabolomics experiment. The mass difference between the corresponding fragment ions present in the MS/MS spectra of the native and U-13C-labeled compound enabled the assignment of the number of carbon atoms to each fragment signal and allowed the generation of meaningful putative molecular formulas for each fragment ion, which in turn also helped determine the elemental composition of the precursor ion. Compared to laborious manual analysis of the MS/MS spectra, the presented algorithm marks an important step toward efficient fragment signal elucidation and structure annotation of metabolites in future untargeted metabolomics studies. Moreover, as demonstrated for a fungal culture sample, FragExtract also assists the characterization of unknown metabolites, which are not contained in databases, and thus exhibits a significant contribution to untargeted metabolomics research. PMID:24965664

Metabolic profiles of flooding-tolerant mechanism in early-stage soybean responding to initial stress.

PubMed

Wang, Xin; Zhu, Wei; Hashiguchi, Akiko; Nishimura, Minoru; Tian, Jingkui; Komatsu, Setsuko

2017-08-01

Metabolomic analysis of flooding-tolerant mutant and abscisic acid-treated soybeans suggests that accumulated fructose might play a role in initial flooding tolerance through regulation of hexokinase and phosphofructokinase. Soybean is sensitive to flooding stress, which markedly reduces plant growth. To explore the mechanism underlying initial-flooding tolerance in soybean, mass spectrometry-based metabolomic analysis was performed using flooding-tolerant mutant and abscisic-acid treated soybeans. Among the commonly-identified metabolites in both flooding-tolerant materials, metabolites involved in carbohydrate and organic acid displayed same profile at initial-flooding stress. Sugar metabolism was highlighted in both flooding-tolerant materials with the decreased and increased accumulation of sucrose and fructose, respectively, compared to flooded soybeans. Gene expression of hexokinase 1 was upregulated in flooded soybean; however, it was downregulated in both flooding-tolerant materials. Metabolites involved in carbohydrate/organic acid and proteins related to glycolysis/tricarboxylic acid cycle were integrated. Increased protein abundance of phosphofructokinase was identified in both flooding-tolerant materials, which was in agreement with its enzyme activity. Furthermore, sugar metabolism was pointed out as the tolerant-responsive process at initial-flooding stress with the integration of metabolomics, proteomics, and transcriptomics. Moreover, application of fructose declined the increased fresh weight of plant induced by flooding stress. These results suggest that fructose might be the critical metabolite through regulation of hexokinase and phosphofructokinase to confer initial-flooding stress in soybean.

Application of an untargeted metabolomics approach for the identification of compounds that may be responsible for observed differential effects in chickens fed an organic and a conventional diet.

PubMed

Ruiz-Aracama, A; Lommen, A; Huber, M; van de Vijver, L; Hoogenboom, R

2012-01-01

The aim of this study was to apply an untargeted NMR and LC-MS-based metabolomics approach to detect potential differences between an organically and a conventionally produced feed, which caused statistically significant differences in growth, in the response to an immunological challenge and in the gene expression profiles in the small intestine of laying hens. A fractionation procedure was set up to create multiple fractions of the feed, which were subsequently analysed by NMR and UPLC-TOF/MS operating in positive mode. Comparison of the profiles revealed that the most apparent differences came from the isoflavones in the soy as well as a compound with a molecular mass of 441.202 (M + 1)⁺, which was identified as N,N'-diferuloylputrescine (DFP) and came from the corn. Whether the observed differences in effects are due to the higher levels of isoflavones and DFP is unclear, as is the fact whether the observed differences are typical for organic or conventional produced corn and soy. However, this study shows that this metabolomics approach is suitable for detecting potential differences between products, even in levels of compounds that would have been overlooked with a more targeted approach. As such, the method is suitable for a more systematic study on differences between conventionally and organically produced food.