Download (.pdf) Data Handling for Interactive Metabolomics: Tools for Studying the Dynamics of Metabolome-Macromolecule Interactions
by Clare Daykin
C.A. Daykin, R. Bro, F. Wulfert (2011), Metabolomics, Available via Online First. DOI: 10.1007/s11306-011-0359-3
All published metabolomics studies investigate changes in either absolute or relative quantities of metabolites.... more All published metabolomics studies investigate changes in either absolute or relative quantities of metabolites. However, blood plasma, one of the most commonly studied biofluids for metabolomics applications, is a complex, heterogeneous mixture of lipoproteins, proteins, small organic molecules and ions which together undergo a variety of possible molecular interactions including metal complexation, chemical exchange processes, micellular compartmentation of metabolites, enzyme-mediated biotransformations and small-molecule-macromolecule binding. In particular, many low molecular weight (MW) compounds (including drugs) can exist both ‘free’ in solution and bound to proteins or within organised aggregates of macromolecules. To study the effects of e.g. disease on these interactions we suggest that new approaches are needed. We have developed a technique termed ‘interactive metabolomics’ or i-metabolomics. i-metabolomics can be defined as: “The study of interactions between low MW biochemicals and macromolecules in heterogeneous biosamples such as blood plasma, without pre-selection of the components of interest”. Standard 1D NMR experiments commonly used in metabolomics allow metabolite concentration differences between samples to be investigated because the intensity of each peak depends on the concentration of the compound in question. On the other hand, the instrument can be set-up to measure molecular interactions by monitoring the diffusion coefficients of molecules. According to the Stokes–Einstein equation, the diffusion coefficient of a molecule is inversely proportional to its effective size, as represented by the hydrodynamic radius. Therefore, when low MW compounds are non-covalently bound to proteins, the observed diffusion coefficient for the compound will be intermediate between those of its free and bound forms. By measuring diffusion by NMR, the degree of protein binding can be estimated for either low MW endogenous biochemicals or xenobiotics. This type of experiment is referred to as either Diffusion-Ordered Spectroscopy (DOSY) or Diffusion-Edited Spectroscopy, depending on the type of post-acquisition data processing applied to the spectra. Results presented in this paper demonstrate approaches for the non-selective modelling of metabolite-macromolecule interactions (i-metabolomics), whilst additionally highlighting some of the all too frequently ignored issues associated with interpretation of data derived from profiling of blood plasma.
Weighted Correlation Network Analysis (WGCNA) Applied to the Tomato Fruit Metabolome
by Gary Strahan
M.V. DiLeo, G.D. Strahan, M. den Bakker, O.A. Hoekenga
PLoS ONE 6(10), pp. e26683 (2011)
doi:10.1371/journal.pone.0026683
1H NMR metabolomics combined with gene expression analysis for the determination of major metabolic differences between subtypes of breast cell lines
by Dan Tulpan
Cuperlovic-Culf, M., Chute, I.C., Culf, A.S., Touaibia, M., Ghosh, A., Griffiths, S., Tulpan, D., Léger, S., Belkaid, A., Surette, M.E., Ouellette, R.J. (2011). 1H NMR metabolomics combined with gene expression analysis for the determination of major metabolic differences between subtypes of breast cell lines. Chemical Science, 2, 2263-2270.
1H NMR analysis was performed on metabolic extracts from a selection of six breast cell lines, including... more 1H NMR analysis was performed on metabolic extracts from a selection of six breast cell lines, including normal-immortalized, invasive ductal carcinomas and adenocarcinomas. Metabolites with significant concentration differences between normal and cancerous cells as well as ER+ and ER− (estrogen receptor) cells were determined and their relation to the differentially expressed genes was explored. Major differences have been shown for many amino acids and this was linked to expression level changes of related genes. Observed changes in choline concentration were connected to expression level changes of the SCL44A1 transporter gene.
MetaboHunter: an automatic approach for identification of metabolites from 1H-NMR spectra of complex mixtures.
by Dan Tulpan
Tulpan, D., Leger, S., Belliveau, L., Culf, A., Cuperlovic-Culf, M. (2011). MetaboHunter: an automatic approach for identification of metabolites from 1H-NMR spectra of complex mixtures. BMC Bioinformatics, 12:400.
Background:
One-dimensional 1H-NMR spectroscopy is widely used for high-throughput characterization of... more
Background:
One-dimensional 1H-NMR spectroscopy is widely used for high-throughput characterization of metabolites in complex biological mixtures. However, the accurate identification of individual compounds is still a challenging task, particularly in spectral regions with higher peak densities. The need for automatic tools to facilitate and further improve the accuracy of such tasks, while using increasingly larger reference spectral libraries becomes a priority of current metabolomics research.
Results:
We introduce a web server application, called MetaboHunter, which can be used for automatic assignment of 1H-NMR spectra of metabolites. MetaboHunter provides methods for automatic metabolite identification based on spectra or peak lists with three different search methods and with possibility for peak drift in a user defined spectral range. The assignment is performed using as reference libraries manually curated data from two major publicly available databases of NMR metabolite standard measurements (HMDB and MMCD). Tests using a variety of synthetic and experimental spectra of single and multi metabolite mixtures show that MetaboHunter is able to identify, in average, more than 80% of detectable metabolites from spectra of synthetic mixtures and more than 50% from spectra corresponding to experimental mixtures. This work also suggests that better scoring functions improve by more than 30% the performance of MetaboHunter’s metabolite identification methods.
Conclusions:
MetaboHunter is a freely accessible, easy to use and user friendly 1H-NMR-based web server application that provides efficient data input and pre-processing, flexible parameter settings, fast and automatic metabolite fingerprinting and results visualization via intuitive plotting and compound peak hit maps. Compared to other published and freely accessible metabolomics tools, MetaboHunter implements three efficient methods to search for metabolites in manually curated data from two reference libraries.
Availability: http://www.nrcbioinformatics.ca/metabohunter/
A Combined 1H Nuclear Magnetic Resonance and Electrospray Ionization–Mass Spectrometry Analysis to Understand the Basal Metabolism of Plant-Pathogenic Fusarium spp.
Molecular Plant Microbe Interactions, 2010
Lowe RG, Allwood JW, Urban M, Daudi A, Canning G, Ward JL, Beale MH and Hammond-Kosack K (2010) A combined proton-NMR and ESI-MS analysis to understand the basal metabolism of Fusarium species. Molecular Plant-Microbe Interactions 23 (12): 1605-1608.
Metabolomics of amniotic fluid and preterm delivery.
Published in Journal of Maternal-Fetal and Neonatal Medicine
Biological variation of Vanilla planifolia leaf metabolome
by Tony PALAMA
published in Phytochemistry, 2010
The metabolomic analysis of Vanilla planifolia leaves collected at different developmental stages was carried out... more The metabolomic analysis of Vanilla planifolia leaves collected at different developmental stages was carried out using 1H-nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis in order to evaluate their variation. Ontogenic changes of the metabolome were considered since leaves of different ages were collected at two different times of the day and in two different seasons. Principal component analysis (PCA) and partial least square modeling discriminate analysis (PLS-DA) of 1H NMR data provided a clear separation according to leaf age, time of the day and season of collection. Young leaves were found to have higher levels of glucose, bis[4-(β-d-glucopyranosyloxy)-benzyl]-2-isopropyltartrate (glucoside A) and bis[4-(β-d-glucopyranosyloxy)-benzyl]-2-(2-butyl)-tartrate (glucoside B), whereas older leaves had more sucrose, acetic acid, homocitric acid and malic acid. Results obtained from PLS-DA analysis showed that leaves collected in March 2008 had higher levels of glucosides A and B as compared to those collected in August 2007. However, the relative standard deviation (RSD) exhibited by the individual values of glucosides A and B showed that those compounds vary more according to their developmental stage (50%) than to the time of day or the season in which they were collected (19%). Although morphological variations of the V. planifolia accessions were observed, no clear separation of the accessions was determined from the analysis of the NMR spectra. The results obtained in this study, show that this method based on the use of 1H NMR spectroscopy in combination with multivariate analysis has a great potential for further applications in the study of vanilla leaf metabolome.
Metabolic Changes in Different Developmental Stages of Vanilla planifolia Pods
by Tony PALAMA
published in Journal of Agricultural and Food Chemistry, 2009
The metabolomic analysis of developing Vanilla planifolia green pods (between 3 and 8 months after pollination) was... more The metabolomic analysis of developing Vanilla planifolia green pods (between 3 and 8 months after pollination) was carried out by nuclear magnetic resonance (NMR) spectroscopy and multivariate data analysis. Multivariate data analysis of the 1H NMR spectra, such as principal component analysis (PCA) and partial least-squares-discriminant analysis (PLS-DA), showed a trend of separation of those samples based on the metabolites present in the methanol/water (1:1) extract. Older pods had a higher content of glucovanillin, vanillin, p-hydroxybenzaldehyde glucoside, p-hydroxybenzaldehyde, and sucrose, while younger pods had more bis[4-(β-d-glucopyranosyloxy)-benzyl]-2-isopropyltartrate (glucoside A), bis[4-(β-d-glucopyranosyloxy)-benzyl]-2-(2-butyl)tartrate (glucoside B), glucose, malic acid, and homocitric acid. A liquid chromatography−mass spectrometry (LC−MS) analysis targeted at phenolic compound content was also performed on the developing pods and confirmed the NMR results. Ratios of aglycones/glucosides were estimated and thus allowed for detection of more minor metabolites in the green vanilla pods. Quantification of compounds based on both LC−MS and NMR analyses showed that free vanillin can reach 24% of the total vanillin content after 8 months of development in the vanilla green pods.
Shoot differentiation from protocorm callus cultures of Vanilla planifolia (Orchidaceae): proteomic and metabolic responses at early stage
by Tony PALAMA
publised in BMC Plant Biology, 2010
Background: Vanilla planifolia is an important Orchid commercially cultivated for the production of natural vanilla... more
Background: Vanilla planifolia is an important Orchid commercially cultivated for the production of natural vanilla flavour. Vanilla plants are conventionally propagated by stem cuttings and thus causing injury to the mother plants. Regeneration and in vitro mass multiplication are proposed as an alternative to minimize damage to mother plants. Because mass production of V. planifolia through indirect shoot differentiation from callus culture is rare and may be a successful use of in vitro techniques for producing somaclonal variants, we have established a novel protocol for the regeneration of vanilla plants and investigated the initial biochemical and molecular mechanisms that trigger shoot organogenesis from embryogenic/organogenic callus.
Results: For embryogenic callus induction, seeds obtained from 7-month-old green pods of V. planifolia were inoculated on MS basal medium (BM) containing TDZ (0.5 mg l-1). Germination of unorganized mass callus such as protocorm -like structure (PLS) arising from each seed has been observed. The primary embryogenic calli have been formed after transferring on BM containing IAA (0.5 mg l-1) and TDZ (0.5 mg l-1). These calli were maintained by subculturing on BM containing IAA (0.5 mg l-1) and TDZ (0.3 mg l-1) during 6 months and formed embryogenic/
organogenic calli. Histological analysis showed that shoot organogenesis was induced between 15 and 20 days after
embryogenic/organogenic calli were transferred onto MS basal medium with NAA (0.5 mg l-1). By associating proteomics and metabolomics analyses, the biochemical and molecular markers responsible for shoot induction have been studied in 15-day-old calli at the stage where no differentiating part was visible on organogenic calli. Twodimensional electrophoresis followed by matrix-assisted laser desorption ionization time-of-flight-tandem mass spectrometry (MALDI-TOF-TOF-MS) analysis revealed that 15 protein spots are significantly expressed (P < 0.05) at earlier stages of shoot differentiation. The majority of these proteins are involved in amino acid-protein metabolism and photosynthetic activity. In accordance with proteomic analysis, metabolic profiling using 1D and 2D NMR techniques showed the importance of numerous compounds related with sugar mobilization and nitrogen metabolism. NMR analysis techniques also allowed the identification of some secondary metabolites such as phenolic compounds whose accumulation was enhanced during shoot differentiation.
Conclusion: The subculture of embryogenic/organogenic calli onto shoot differentiation medium triggers the stimulation of cell metabolism principally at three levels namely (i) initiation of photosynthesis, glycolysis and phenolic compounds synthesis; (ii) amino acid - protein synthesis, and protein stabilization; (iii) sugar degradation. These biochemical mechanisms associated with the initiation of shoot formation during protocorm - like body (PLB) organogenesis could be coordinated by the removal of TDZ in callus maintenance medium. These results might contribute to elucidate the complex mechanism that leads to vanilla callus differentiation and subsequent shoot formation into PLB organogenesis. Moreover, our results highlight an early intermediate metabolic event in vanillin biosynthetic pathway with respect to secondary metabolism. Indeed, for the first time in vanilla tissue culture, phenolic compounds such as glucoside A and glucoside B were identified. The degradation of these compounds in specialized tissue (i.e. young green beans) probably contributes to the biosynthesis of glucovanillin, the parent compound of vanillin.
PhD thesis : "NMR-based metabolomic characterization of Vanilla planifolia"
by Tony PALAMA
Defence date: 10th June 2010
Metabolic Characterization of Green Pods from Vanilla planifolia Accessions Grown in La Réunion
by Tony PALAMA
published in Environmental and Experimental Botany, 2011
Large phenotypic variation has been observed between the cultivated vanillas since a single genetic source of Vanilla... more Large phenotypic variation has been observed between the cultivated vanillas since a single genetic source of Vanilla planifolia was spread to the Indian Ocean and the Indonesia in the 19th century. In order to differentiate the cultivated vanilla plants, genetic studies have been conducted in the past on the plants grown in various regions such as the French island, La Réunion. However, the genetic difference was not big enough to differentiate diverse accessions of V. planifolia. In this study, metabolomics, in which genetic variation could be amplified, was employed to delve into the variation between the cultivated vanilla plants. To obtain a broad view of the metabolome, nuclear magnetic resonance (NMR) spectroscopy was applied to the analysis of V. planifolia green pods. Principal component analysis (PCA) and partial least square-discriminant analysis (PLS-DA) of the data showed that the accessions could be differentiated according to their glucovanillin and glucosides A and B contents. Furthermore, a correlation between the glucovanillin content and the pod length, number of flower and growth capacity of the accessions has been observed from the multivariate data analysis.
SiDMAP: a metabolomics approach to assess the effects of drug candidates on the dynamic properties of biochemical pathways
by Greg Maguire
Published In: Expert Opinion on Drug Discovery
The postgenomic era in drug development is characterised by a need to describe and predict the functional actions of a... more The postgenomic era in drug development is characterised by a need to describe and predict the functional actions of a given compound within the complex systems of the organism. Recent advances in analytical and computational techniques have given rise to a new and powerful tool for the measurement of biochemical pathways in cells, animals and humans. The stable isotope dynamic metabolic profiling (SiDMAP) assay measures the flow of molecules through complex metabolic pathways, rather than just measuring the gene or protein in isolation. Thus, the SiDMAP assay is a measurement of the phenotype in biology, disease and the treatment of disease. The SiDMAP assay differs from other static approaches in two key ways: i) SiDMAP measures the activity of pathways in fully intact systems, rather than just the component pieces of the system; and ii) SiDMAP measures molecular flux observed in the dimension of time, as apposed to measuring overall levels of metabolites in a system and then trying to predict functionality. These two features confer unparalleled sensitivity to the SiDMAP analysis and have allowed for the discovery of the activity of biochemical pathways important to a number of diseases, including cancer and the metabolic syndrome and how to best treat these diseases targeting the system of pathways. Thus, SiDMAP is a technology that can be widely used in the drug discovery and development process to better describe the biochemistry of disease states, determine the method of action of compounds, detect possible toxicity early in the drug development process, reposition compounds, develop biomarkers stratify patients and to enable Phase IV studies.
Development of Tracer-Based Metabolomics and its Implications for the Pharmaceutical Industry
by Greg Maguire
Published in: International J. of Pharmaceutical Medicine 2007
In the post-genomic era, increasing our understanding of genotype-phenotypic correlation and its changes in diseases... more
In the post-genomic era, increasing our understanding of genotype-phenotypic correlation and its changes in diseases is of the highest priority in drug development. The phenotype of an organism consists of its physical/chemical attributes and its functional attributes. Metabolomics is a promising research tool for the phenotypic characterisation of an organism providing physical and functional assessment of a cellular metabolic network. Metabolomics has evolved from analytical biochemistry.
With advances in nuclear magnetic resonance spectroscopy and mass spectrometry, metabolomics provides comprehensive analyses that detect and measure a wide range of small molecules (metabolites) in bodily fluid or tissue extracts. With automation, metabolomics analysis has the potential of a high throughput screening tool for measuring the effects of drugs in cells or in whole organisms, including humans. There are two major forms of metabolomics: metabolite profiling, which includes 'fingerprinting', and metabolic profiling, which includes tracer-based metabolomics. In this review, techniques and concepts for each of these modalities is reviewed. Examples of the applications of metabolomics in the characterisation of phenotype, determining the mode of action of compounds and detection of drug toxicity are presented.
Application of metabolite profiling to the identification of traits in a population of tomato introgression lines
Journal of Experimental Botany 2005 56 (410): 287-296
Naturally occurring variation in wild species can be used to increase the genetic diversity of cultivated crops and... more Naturally occurring variation in wild species can be used to increase the genetic diversity of cultivated crops and improve agronomic value. Populations of introgression lines carrying wild species alleles afford an opportunity to identify traits associated with the introgressed regions, and facilitate characterization of the biochemistry and genetics underlying these phenotypes. Understanding plant metabolic pathways and the interactions between genes, phenotype, and environment is fundamental to functional genomics. Successful analysis of the complex network of plant metabolism requires analytical methods able to record information on as many metabolites as possible. Metabolite profiling is used to provide a snapshot of the metabolome in samples which differ in a known factor such as genetic background. Differences between the metabolite profiles can identify those metabolites/metabolic pathways affected by the introgression and allow genetic maps for metabolic alterations to be established. A Time-of-Flight Mass Spectrometry method is presented, with associated data reduction, used for profiling aqueous metabolites fom tomato. Analysis of ripe fruits of two tomato species, Lycopersicon esculentum and L. pennellii, showed differences in the amounts of many metabolites, including organic acids and sugars. Six introgression lines, L. pennellii introgressions within L. esculentum, were also examined and showed that Principal Component Analysis can reveal subtle differences in metabolism of the introgressed lines when compared to their parents.
Probing the metabolic aberrations underlying mutant huntingtin toxicity in yeast and assessing their degree of preservation in humans and mice.
Co-authored with Ronni M. Matheke, Lindsey M. Smith, and Robert H. Cichewicz
Metabolomics is a powerful multi-parameter tool for evaluating phenotypic traits associated with disease... more Metabolomics is a powerful multi-parameter tool for evaluating phenotypic traits associated with disease processes. We have used 1H NMR metabolome profiling to characterize metabolic aberrations in a yeast model of Huntington’s disease that are attributable to the mutant huntingtin protein’s gain-of-toxic-function effects. A group of 11 metabolites (alanine, acetate, galactose, glutamine, glycerol, histidine, proline, succinate, threonine, trehalose, and valine) exhibited significant concentration changes in yeast expressing the N-terminal fragment of a mutant human huntingtin gene. Correspondence analysis was used to compare results from our yeast model to data reported from transgenic mice expressing a mutant huntingtin gene fragment and Huntington’s disease patients. This technique enabled us to identify a variety of both model specific (pertaining to a single species) and conserved (observed in multiple species) biomarkers related to mutant huntingtin’s toxicity. Among the 59 metabolites identified, four compounds (alanine, glutamine, glycerol, and valine) changed significantly in concentration in all three Huntington’s disease systems. We propose that alanine, glutamine, glycerol, and valine should be considered as promising biomarkers for evaluating new Huntington’s disease therapies, as well as providing unique insight into the mechanisms associated with mutant huntingtin toxicity.