Current Metabolomics - Volume 3, Issue 1, 2015

The importance of nucleoside metabolism in brain followed the recognition that i) adult nervous system maintains its nucleotide pools in the proper qualitative and quantitative balance by salvaging preformed purine and pyrimidine rings, rather than by synthesizing nucleosides de novo from simple precursors, ii) adenosine, a purine nucleoside, acts as an extracellular signal, and exerts its protective effects by interacting with plasmamembrane bound purinergic G-protein coupled P2X receptors. More recently uridine, a pyrimidine nucleoside, has received considerable attention. Most of the uridine content of brain is supplied by its uptake from the plasma. An increasing body of evidence suggests that uridine exerts its function intracellularly in three distinct ways. It is phosphorylated to UTP, a pyrimidine nucleotide acting as a precursors for RNA and DNA synthesis, and as an extracellular neurotrophic signal. In combination with the ω-3 fatty acid decosahexaenoic acid and choline, uridine accelerates formation of synaptic membrane, being an obligatory precursor for CDP-choline synthesis. Finally, uridine can preserve the ATP pool via the conversion of its ribose-1-phosphate moiety into energetic intermediates of glycolysis. This article summarizes our present knowledge on uridine metabolism in the brain, with special emphasis on the mechanisms maintaining its intracellular homeostasis and on the cross talk between intracellular and extracellular uridine metabolism.

While data processing methods in metabolomic studies often work with 'n' number of dimensions, analytical techniques, with the notable exception of NMR, have mostly stuck only to one. Peak overlap continues to be a problem and there is an ever-present demand to maximize the number of metabolites that can be separated and identified in a single run. One method that might help to overcome these issues is multidimensional liquid chromatography, which uses two columns of different phases. A sequential collection of aliquots is made from the first column and reinjected onto a second, and the resulting data are then plotted in 2D or 3D space. The total peak capacity of such a system is the combined peak capacities of each column. The 'offline' version of this technique, using a fraction collector, was introduced over 30 years ago but with recent advances in instrumentation and software, particularly the 'online' approach using automated switching valves, has led to increasing interest in the technique. Both offline and online methods can be carried out as a comprehensive procedure, or via 'heart-cutting', in which only specific peaks are analysed in the second dimension. Past applications include proteomics, natural product chemistry, forensic science and pharmaceutical analysis. These successes are likely to be built on in the future as new column chemistries and bio-informatic approaches are developed. In this review an overview of the theory of twodimensional liquid chromatography is presented, its potential in the field of metabolomics is assessed and predictions for future research directions are made.

In high-throughput scenarios, a large number of similar NMR spectra from a single study need to be analyzed. The complexity of the data required the use of spectral databases to characterize resonances of interest and extract quantitative information. The recently reported CRAFT (Complete Reduction to Amplitude Frequency Table) technique, based on a Bayesian analysis approach, converts a time-domain FID to a frequency-amplitude table in a robust, automated, and time-efficient fashion. We report the application of the CRAFT technique to the extraction of quantitative information from the NMR spectra of complex mixtures – the targeted analysis of spent media from mammalian cell cultures and the untargeted profiling of soy supplement extracts. CRAFT, in a significantly automated fashion, converts the raw NMR spectra into a data-mining-friendly spreadsheet format with high fidelity and accuracy. The reported examples clearly demonstrate that the automated, time-domain data reduction by the CRAFT technique gives comparable results to traditional approaches. Moreover, the approach described herein allows for iterative adjustment of the post- CRAFT NMR parametric filters of the tabular data (such as linewidth and/or amplitude and/or frequency window thresholds) for reexamination. Such iterative parametric filters in conjunction with statistical analysis/guidance have the potential opportunity to develop analyte fingerprint databases for subsequent sample screening and library comparisons. Thus, this technique potentially allows for the development of rapid screening methods, both targeted and untargeted, to be implemented easily, and be employed effectively in high throughput environments.

Polar metabolite profiles (amino acids, organic acids, phenols, sugars and sugar alcohols) and nonpolar metabolites (mainly fatty acids) of 11 different varieties of Onion (Allium cepa L.) bulb developed in India, were analyzed using GC-MS based metabolomics approach. PLS-DA score plot was used for visual assessments of clustering trends. The metabolites contributing for formation of segregated clustering scores were identified (p<0.05). The analyses were carried out to organize the analyzed samples in groups based on the similarities and differences in primary metabolite profiles, and to verify which metabolites accounted for maximum variability of the profiles. Distinct differences in the levels of different metabolites existed in the varieties with respect to gallic acid, organic acid, amino acid, sugar and sugar alcohol profiles. The present study suggests existence of biochemical differences in different onion varieties. Distinct clustering trends were also prominent separating varieties developed in different regions in India.

Nine samples of propolis from different parts of the UK were extracted and profiled by high resolution LC-MS. The data were aligned and features were extracted into 0.02 amu windows. The profiles contained thousands of features. In order to establish a platform for comparison of the samples the top 125 features by average peak intensity across the samples, after excluding abundant dimer peaks, were selected for further characterisation by MS2. Of the top 125 features around 90% of the peaks could be assigned an identity with some degree of confidence. Only ca 50% of these putatively identified compounds had been reported in propolis before. The compounds fell into a few major categories: flavonoid esters and possibly some flavonoid ethers, phenyl propanoid esters, glycerol esters, flavonoid glycosides and hydroxylated fatty acids. Pinobanksin was the most abundant compound by average response across nine samples. The flavonoids pinocembrin, pinobanksin, galangin and chrysin showed a relatively low degree of variation across the samples whereas some compounds such as flavonoid esters and glycerol esters were much more variable in their abundance. The role of propolis in preventing infections in the bee hive has yet to be established but the approach taken in this paper provides a potential method for trying to correlate hive health with the composition of the propolis gathered by the hive if suitable metadata were collected.

The field of metabolomics has continued to expand rapidly in the past two years. It has become an important part of personalized, predictive, preventive, and participatory (P4) medicine. In this article, recent advances in analytical methods (capillary electrophoresis, gas chromatography, liquid chromatography, mass spectrometry and MS imaging) are described. Advances in data analysis, quality control and receiver operator characteristic (ROC) curves are also described. The recent uses of metabolomics in disease diagnosis, epidemiology, epigenetics, hypertension, cancer, toxicology, drug discovery and the understanding of biological processes are also presented.

Infection by the Human Immunodeficiency Virus (HIV) and subsequent treatment with Highly Active Antiretroviral therapy (HAART) can lead to the development of metabolic abnormalities. The ability to diagnose and monitor these complications remains cumbersome and is limited to the detection of one or only a few metabolites at a time. The discovery and development of reliable HIV and/or HAART related biomarkers, using metabolic profiling techniques (known for the simultaneous detection of numerous metabolites), could assist in improving the management of HIV/AIDS. Here, Raman spectroscopy based metabonomics was conducted and the metabolic profiles of 35 HIVinfected, treatment-experienced (HIV+ART+) and treatment-naïve sera (HIV+ART-) compared to those of 17 uninfected (HIV-) individuals. The Raman spectral profiles were subjected to multivariate data analysis for the identification of metabolites that differed significantly amongst the three groups. Linear discriminant analysis (LDA) correctly classified all samples into their respective experimental groups with a 100% accuracy. Analysis of variance (ANOVA) identified significant differences (p< 0.05) in spectral variables associated with tryptophan (1603cm-1, 1550-1554cm-1, 1208cm-1, 1174cm-1), glutathione (828cm-1, 890cm-1, 900cm-1), lysine (1570cm-1), histidine (1574cm-1), protein components (1685cm-1, 1474, 948-1), glucose (1295cm-1), threonine/proline (1548cm-1), valine (948cm-1), tyrosine (831cm-1, 641cm-1, 635cm-1), lipids (716cm-1) and phenylalanine (616cm-1). The metabolic pathways where these metabolites play a role have been shown by conventional biochemical analysis to be affected by HIV and HAART. An assay using Ellman’s reagent (5, 5’-dithiobis-(2-nitrobenzoic acid) confirmed the Raman spectral detection of differences in glutathione. The Glutathione levels were significantly (p<0.05) reduced in HIV infected samples, which were indicative of oxidative stress. The ability of Raman spectroscopy to detect metabolites (including an oxidative stress marker) affected by HIV/AIDS and HAART, adds to the growing list of pathologies where vibrational spectroscopy may contribute solutions.