Dynamic metabolic patterns tracking neurodegeneration and gliosis following 26S proteasome dysfunction in mouse forebrain neurons.

Metabolite profiling is an important tool that may better capture the multiple features of neurodegeneration. With the considerable parallels between mouse and human metabolism, the use of metabolomics in mouse models with neurodegenerative pathology provides mechanistic insight and ready translation into aspects of human disease. Using 400 MHz nuclear magnetic resonance spectroscopy we have carried out a temporal region-specific investigation of the metabolome of neuron-specific 26S proteasome knockout mice characterised by progressive neurodegeneration and Lewy-like inclusion formation in the forebrain. An early significant decrease in N-acetyl aspartate revealed evidence of neuronal dysfunction before cell death that may be associated with changes in brain neuroenergetics, underpinning the use of this metabolite to track neuronal health. Importantly, we show early and extensive activation of astrocytes and microglia in response to targeted neuronal dysfunction in this context, but only late changes in myo-inositol; the best established glial cell marker in magnetic resonance spectroscopy studies, supporting recent evidence that additional early neuroinflammatory markers are needed. Our results extend the limited understanding of metabolite changes associated with gliosis and provide evidence that changes in glutamate homeostasis and lactate may correlate with astrocyte activation and have biomarker potential for tracking neuroinflammation.

Enhanced NMR-based profiling of polyphenols in commercially available grape juices using solid-phase extraction.

Grapes and related products, such as juices, and in particular, their polyphenols, have previously been associated with many health benefits, such as protection against cardiovascular disease. Within grapes, a large range of structurally diverse polyphenols can be present, and their characterisation stands as a challenge. (1)H NMR spectroscopy in principle would provide a rapid, nondestructive and straightforward method for profiling of polyphenols. However, polyphenol profiling and identification in grape juices is hindered because of signals of prevailing carbohydrates causing spectral overlap and compromising dynamic range. This study describes the development of an extraction method prior to analysis using (1)H NMR spectroscopy, which can, potentially, significantly increase the number of detectable polyphenols and aid their identification, by reduction of signal overlap and selective removal of heavily dominating compounds such as sugars.

Nutrimetabolomics: development of a bio-identification toolbox to determine the bioactive compounds in grape juice.

BACKGROUND: Grape juice and related products have previously been associated with many health benefits, such as protection against cardiovascular disease. Current consensus is that the polyphenols are the likely bioactive species in these products. RESULTS: Extracts of commercially available grape juices exhibited biological antioxidant activities ranging from 19.30 to 3099.51 µM trolox equivalents, as determined by cell-based assay in which J774 macrophages were stimulated with lipopolysaccaride at a concentration of 100 µg/ml for 1 h. Partial least-squares regression was then used to determine covariance between the antioxidant activity and 400 MHz (1)H NMR spectral profiles using models with R(2)X and R(2)Y values of 0.64 and 0.95, respectively, using three latent variables: the Q(2)(cum) was 0.63. Hydroxycinnamic acids and their derivatives were identified as being the most positively correlated with the antioxidant activity. CONCLUSION: The work presented here describes a strategy for the bioinformatic linkage of plant metabolomic data with in vitro biological activity as an initial step towards determining structure-activity relationships.

Measurement of ischaemia-reperfusion in patients with intermittent claudication using NMR-based metabonomics.

Intermittent claudication has proved to be a good in vivo model for ischaemia-reperfusion. For assessment of ischaemia-reperfusion damage, the known biochemical markers all have disadvantages with respect to sensitivity and interference with other physiological events. In this work, we studied the metabolic effects of ischaemia-reperfusion in patients with intermittent claudication, and the effects of vitamin C and E intervention, using both traditional biochemical measurements and 1H-NMR-based metabonomics on urine and plasma. The 1H-NMR spectra were subjected to multivariate modelling using principal components discriminant analysis, and the observed clusters were validated using joint deployment of univariate analysis of variance and Tukey-Kramer honestly significant difference (HSD) testing. The study involved 14 patients with intermittent claudication and three healthy volunteers, who were monitored during a walking test, before and after a vitamin C/E intervention, and after a washout period. The effect of exercise was only observable for a limited number of biochemical markers, whereas 1H NMR revealed an effect in line with anaerobic ATP production via glycolysis in exercising (ischaemic) muscle of the claudicants. Thus, the beneficial effect of vitamins C and E in claudicants was more pronounced when observed by metabonomics than by traditional biochemical markers. The main effect was more rapid recovery from exercise to resting state metabolism. Furthermore, after intervention, claudicants tended to have lower concentrations of lactate and glucose and several other citric acid cycle metabolites, whereas acetoacetate was increased. The observed metabolic changes in the plasma suggest that intake of vitamin C/E leads to increased muscle oxidative metabolism.

Proposed minimum reporting standards for chemical analysis Chemical Analysis Working Group (CAWG) Metabolomics Standards Initiative (MSI).

There is a general consensus that supports the need for standardized reporting of metadata or information describing large-scale metabolomics and other functional genomics data sets. Reporting of standard metadata provides a biological and empirical context for the data, facilitates experimental replication, and enables the re-interrogation and comparison of data by others. Accordingly, the Metabolomics Standards Initiative is building a general consensus concerning the minimum reporting standards for metabolomics experiments of which the Chemical Analysis Working Group (CAWG) is a member of this community effort. This article proposes the minimum reporting standards related to the chemical analysis aspects of metabolomics experiments including: sample preparation, experimental analysis, quality control, metabolite identification, and data pre-processing. These minimum standards currently focus mostly upon mass spectrometry and nuclear magnetic resonance spectroscopy due to the popularity of these techniques in metabolomics. However, additional input concerning other techniques is welcomed and can be provided via the CAWG on-line discussion forum at http://msi-workgroups.sourceforge.net/ or http://Msi-workgroups-feedback@lists.sourceforge.net. Further, community input related to this document can also be provided via this electronic forum.

Metabonomics approach to determine metabolic differences between green tea and black tea consumption.

The purpose of this study was to compare the effects of black and green tea consumption on human metabolism. Seventeen healthy male volunteers consumed black tea, green tea, or caffeine in a randomized crossover study. Twenty-four-hour urine and blood plasma samples were analyzed by NMR-based metabonomics, that is, high-resolution 1H NMR metabolic profiling combined with multivariate statistics. Green and black tea consumption resulted in similar increases in urinary excretion of hippuric acid and 1,3-dihydroxyphenyl-2-O-sulfate, both of which are end products of tea flavonoid degradation by colonic bacteria. Several unidentified aromatic metabolites were detected in urine specifically after green tea intake. Interestingly, green and black tea intake also had a different impact on endogenous metabolites in urine and plasma. Green tea intake caused a stronger increase in urinary excretion of several citric acid cycle intermediates, which suggests an effect of green tea flavanols on human oxidative energy metabolism and/or biosynthetic pathways.

Nuclear magnetic resonance spectroscopic based studies of the metabolism of black tea polyphenols in humans.

Epidemiological studies indicate that a high intake of flavonoids is associated with an improved health status. Tea is one of the most abundant sources of flavonoids in the human diet. The bioavailability and biotransformation of tea flavonoids are, however, not clearly understood. The aim of the present study was to investigate the metabolism of black tea via a nonspecific screening method. (1)H nuclear magnetic resonance (NMR) spectroscopy was used to obtain nonselective profiles of urine samples collected from three human volunteers before and after a single dose of black tea. The complex spectroscopic profiles were interpreted with the use of pattern recognition techniques. Hippuric acid was confirmed as the major urinary black tea metabolite. One previously unknown metabolite was detected and identified as 1,3-dihydroxyphenyl-2-O-sulfate (sulfate conjugate of pyrogallol) using HPLC directly coupled to mass spectrometry and (1)H NMR spectroscopy. This study shows that NMR-pattern recognition studies can be used for the discovery of unknown flavonoid metabolites in humans.

Method development in high-performance liquid chromatography for high-throughput profiling and metabonomic studies of biofluid samples.

"Metabonomics" has in the past decade demonstrated enormous potential in furthering the understanding of, for example, disease processes, toxicological mechanisms, and biomarker discovery. The same principles can also provide a systematic and comprehensive approach to the study of food ingredient impact on consumer health. However, "metabonomic" methodology requires the development of rapid, advanced analytical tools to comprehensively profile biofluid metabolites within consumers. Until now, NMR spectroscopy has been used for this purpose almost exclusively. Chromatographic techniques and in particular HPLC, have not been exploited accordingly. The main drawbacks of chromatography are the long analysis time, instabilities in the sample fingerprint and the rigorous sample preparation required. This contribution addresses these problems in the quest to develop generic methods for high-throughput profiling using HPLC. After a careful optimization process, stable fingerprints of biofluid samples can be obtained using standard HPLC equipment. A method using a short monolithic column and a rapid gradient with a high flow-rate has been developed that allowed rapid and detailed profiling of larger numbers of urine samples. The method can be easily translated into a slow, shallow-gradient high-resolution method for identification of interesting peaks by LC-MS/NMR. A similar approach has been applied for cell culture media samples. Due to the much higher protein content of such samples non-porous polymer-based small particle columns yielded the best results. The study clearly shows that HPLC can be used in metabonomic fingerprinting studies.

The comparison of plasma deproteinization methods for the detection of low-molecular-weight metabolites by (1)H nuclear magnetic resonance spectroscopy.

Blood plasma is the major vehicle by which metabolites are transported around the body in mammalian species, and chemical analysis of plasma can provide a wealth of information relating to the biochemical status of an individual and is important for diagnostic purposes. However, plasma is very complex in physicochemical terms because it is composed of a range of organic and inorganic constituents with a wide range of molecular weights and chemical classes and this makes analysis non-trivial. It is now well established that high-resolution (1)H NMR spectroscopy of blood plasma provides useful qualitative and quantitative biochemical information relating to metabolic disorders. However, one of the problems encountered in NMR spectroscopic analysis of blood plasma is the extensive peak overlap or presence of broad macromolecule peaks in the (1)H NMR spectrum, which can severely limit the amount of obtainable information. Even with spectroscopic editing, information relating to low-molecular-weight (MW) metabolites is frequently lost. Therefore, the efficiency of a range of conventional protein removal methods, in combination with the use of one- and two-dimensional NMR spectroscopic methods for evaluation, have been compared for the extraction of NMR-observable low-MW metabolites. It has been shown that these "deproteinization" methods vary considerably in recovery of low MW metabolites and a judicious choice is crucial for optimal extraction of a given analyte. The results presented here show that while ultrafiltration provides the "safest" method of plasma deproteinization, the signal-to-noise ratio of the resultant (1)H NMR spectra is poor. On the other hand, acetonitrile precipitation at physiological pH allows the detection of more low-MW metabolites and at higher concentrations than any other method and provides the further advantages of being a rapid and simple procedure.