The comparative metabonomics of age-related changes in the urinary composition of male Wistar-derived and Zucker (fa/fa) obese rats

Urine Metabolites and Bioactive Compounds from Functional Food: Applications of Liquid Chromatography Mass Spectrometry

Bioactive compounds in functional foods, medicinal plants and others are considered attractive value-added molecules based on their wide range of bioactivity. It is clear that an important role is occupied by polyphenol, phenolic compounds and others. Urine is an effective biofluid to evaluate and monitor alterations in homeostasis and other processes related to metabolism. The current review provides a detailed description of the formation of urine in human body, various aspects relevant to sampling and analysis of urinary metabolites before presenting recent developments leveraging on metabolite profiling of urine. For the profiling of small molecules in urine, advancement of liquid chromatography mass tandem spectrometry (LC/MS/MS), establishment of standardized chemical fragmentation libraries, computational resources, data-analysis approaches with pattern recognition tools have made it an attractive option. The profiling of urinary metabolites gives an overview of the biomarkers associated with the diet and evaluates its biological effects. Metabolic pathways such as glycolysis, tricarboxylic acid cycle, amino acid metabolism, energy metabolism, purine metabolism and others can be evaluated. Finally, a combination of metabolite profiling with chemical standardization and bioassay in functional food and medicinal plants will likely lead to the identification of new biomarkers and novel biochemical insights.

Metabolomic Study of Aging in fa/fa Rats: Multiplatform Urine and Serum Analysis

Zucker fatty (fa/fa) rats represent a well-established and widely used model of genetic obesity. Because previous metabolomic studies have only been published for young fa/fa rats up to 20 weeks of age, which can be considered early maturity in male fa/fa rats, the aim of our work was to extend the metabolomic characterization to significantly older animals. Therefore, the urinary profiles of obese fa/fa rats and their lean controls were monitored using untargeted NMR metabolomics between 12 and 40 weeks of age. At the end of the experiment, the rats were also characterized by NMR and LC-MS serum analysis, which was supplemented by a targeted LC-MS analysis of serum bile acids and neurotransmitters. The urine analysis showed that most of the characteristic differences detected in young obese fa/fa rats persisted throughout the experiment, primarily through a decrease in microbial co-metabolite levels, the upregulation of the citrate cycle, and changes in nicotinamide metabolism compared with the age-related controls. The serum of 40-week-old obese rats showed a reduction in several bile acid conjugates and an increase in serotonin. Our study demonstrated that the fa/fa model of genetic obesity is stable up to 40 weeks of age and is therefore suitable for long-term experiments.

Effect of Acylated and Nonacylated Anthocyanins on Urine Metabolic Profile during the Development of Type 2 Diabetes in Zucker Diabetic Fatty Rats

The effect of nonacylated and acylated anthocyanins on urinary metabolites in diabetic rats was investigated. Nonacylated anthocyanins extract from bilberries (NAAB) or acylated anthocyanins extract from purple potatoes (AAPP) was given to Zucker diabetic fatty (ZDF) rats for 8 weeks at daily doses of 25 and 50 mg/kg body weight. ¹H NMR metabolomics was applied to study alterations in urinary metabolites from three time points (weeks 1, 4, and 8). Both types of anthocyanins modulated the metabolites associated with the tricarboxylic acid cycle, gut microbiota metabolism, and renal function at weeks 1 and 4, such as 2-oxoglutarate, fumarate, alanine, trigonelline, and hippurate. In addition, only a high dose of AAPP decreased monosaccharides, formate, lactate, and glucose levels at week 4, suggesting improvement in energy production in mitochondria, glucose homeostasis, and oxidative stress. This study suggested different impacts of AAPP and NAAB on the metabolic profile of urine in diabetes.

Cutaneous Thermal Injury Modulates Blood and Skin Metabolomes Differently in a Murine Model

As the field of metabolomics develops further, investigations of how the metabolome is affected following thermal injury may be helpful to inform diagnostics and guide treatments. In this study, changes to the metabolome were tested and validated in a murine burn injury model. After a 30% total body surface scald injury or sham procedure sera and skin biopsies were collected at 1, 2, 6, or 24 hr.

Burn-specific changes in the metabolome were detected compared to sham animals. The sera metabolome exhibited a more rapid response to burn injury than that of the skin and it peaked more proximal to injury (6 vs 24 hr). Progression of metabolic response in the skin was less synchronous and showed a higher overlap of the significantly modified metabolites (SMMs) among tested time-points. Top affected pathways identified by SMMs of skin included inositol phosphate metabolism, ascorbate and alderate metabolism, caffeine metabolism, and the pentose phosphate pathway. Future research is warranted in human and larger animal models to further elucidate the role of metabolomic perturbations and the pathophysiology following burn injury.

Study on Hypoglycemic Effect of the Drug Pair of Astragalus Radix and Dioscoreae Rhizoma in T2DM Rats by Network Pharmacology and Metabonomics

Type 2 diabetes mellitus (T2DM) is a metabolic disease accompanied by a series of diseases such as diabetic nephropathy. The drug pair (HS) of Astragalus Radix (HQ) and Dioscoreae Rhizoma (SY) was designed by Dr. Shi Jinmo to improve the treatment of T2DM. However, the exact mechanism involved requires further clarification. In this work, 1H-NMR-based metabonomics and network pharmacology were adopted. Metabolic profiling indicated that the metabolic perturbation was reduced after HS treatment. The results found 21 biomarkers. According to the network pharmacology, we found that the regulation of T2DM was primarily associated with 18 active compounds in HS. These active compounds mainly had an effect on 135 targets. Subsequently, combining network pharmacology and metabonomics, we found four target proteins, which indicated that HS has potential hypoglycemic effects through regulating monoamine oxidases B (MAOB), acetyl-CoA carboxylase 1 (ACACA), carbonic anhydrase 2 (CA2), and catalase (CAT). In conclusion, the result showed that these four targets might be the most relevant targets for the treatment of T2DM with HS. This study clarified the mechanism of HS in the treatment of T2DM and also confirmed the feasibility of combining metabonomics and network pharmacology to study the mechanisms of traditional Chinese medicine (TCM). In the future, this approach may be a potentially powerful tool to discovery active components of traditional Chinese medicines and elucidate their mechanisms.

Metabolic signatures suggest o-phosphocholine to UDP-N-acetylglucosamine ratio as a potential biomarker for high-glucose and/or palmitate exposure in pancreatic β-cells

INTRODUCTION

Chronic exposure to high-glucose and free fatty acids (FFA) alone/or in combination; and the resulting gluco-, lipo- and glucolipo-toxic conditions, respectively, have been known to induce dysfunction and apoptosis of β-cells in Diabetes. The molecular mechanisms and the development of biomarkers that can be used to predict similarities and differences behind these conditions would help in easier and earlier diagnosis of Diabetes.

OBJECTIVES

This study aims to use metabolomics to gain insight into the mechanisms by which β-cells respond to excess-nutrient stress and identify associated biomarkers.

METHODS

INS-1E cells were cultured in high-glucose, palmitate alone/or in combination for 24 h to mimic gluco-, lipo- and glucolipo-toxic conditions, respectively. Biochemical and cellular experiments were performed to confirm the establishment of these conditions. To gain molecular insights, abundant metabolites were identified and quantified using ¹H-NMR.

RESULTS

No loss of cellular viability was observed in high-glucose while exposure to FFA alone/in combination with high-glucose was associated with increased ROS levels, membrane damage, lipid accumulation, and DNA double-strand breaks. Forty-nine abundant metabolites were identified and quantified using ¹H-NMR. Chemometric pair-wise analysis in glucotoxic and lipotoxic conditions, when compared with glucolipotoxic conditions, revealed partial overlap in the dysregulated metabolites; however, the dysregulation was more significant under glucolipotoxic conditions.

CONCLUSION

The current study compared gluco-, lipo- and glucolipotoxic conditions in parallel and elucidated differences in metabolic pathways that play major roles in Diabetes. o-phosphocholine and UDP-N-acetylglucosamine were identified as common dysregulated metabolites and their ratio was proposed as a potential biomarker for these conditions.

Association of cultured myotubes and fasting plasma metabolite profiles with mitochondrial dysfunction in type 2 diabetes subjects

Accumulating evidence implicates mitochondrial dysfunction-induced insulin resistance in skeletal muscle as the root cause for the greatest hallmarks of type 2 diabetes (T2D). However, the identification of specific metabolite-based markers linked to mitochondrial dysfunction in T2D has not been adequately addressed. Therefore, we sought to identify the markers-based metabolomics for mitochondrial dysfunction associated with T2D. First, a cellular disease model was established using human myotubes treated with antimycin A, an oxidative phosphorylation inhibitor. Non-targeted metabolomic profiling of intracellular-defined metabolites on the cultured myotubes with mitochondrial dysfunction was then determined. Further, a targeted MS-based metabolic profiling of fasting blood plasma from normal (n = 32) and T2D (n = 37) subjects in a cross-sectional study was verified. Multinomial logical regression analyses for defining the top 5% of the metabolites within a 95% group were employed to determine the differentiating metabolites. The myotubes with mitochondrial dysfunction exhibited insulin resistance, oxidative stress and inflammation with impaired insulin signalling activities. Four metabolic pathways were found to be strongly associated with mitochondrial dysfunction in the cultured myotubes. Metabolites derived from these pathways were validated in an independent pilot investigation of the fasting blood plasma of healthy and diseased subjects. Targeted metabolic analysis of the fasting blood plasma with specific baseline adjustment revealed 245 significant features based on orthogonal partial least square discriminant analysis (PLS-DA) with a p-value < 0.05. Among these features, 20 significant metabolites comprised primarily of branched chain and aromatic amino acids, glutamine, aminobutyric acid, hydroxyisobutyric acid, pyroglutamic acid, acylcarnitine species (acetylcarnitine, propionylcarnitine, dodecenoylcarnitine, tetradecenoylcarnitine hexadecadienoylcarnitine and oleylcarnitine), free fatty acids (palmitate, arachidonate, stearate and linoleate) and sphingomyelin (d18:2/16:0) were identified as predictive markers for mitochondrial dysfunction in T2D subjects. The current study illustrates how cellular metabolites provide potential signatures associated with the biochemical changes in the dysregulated body metabolism of diseased subjects. Our finding yields additional insights into the identification of robust biomarkers for T2D associated with mitochondrial dysfunction in cultured myotubes.

Metabolomics – the complementary field in systems biology: a review on obesity and type 2 diabetes

This paper highlights the metabolomic roles in systems biology towards the elucidation of metabolic mechanisms in obesity and type 2 diabetes.

Importance of sulfur-containing metabolites in discriminating fecal extracts between normal and type-2 diabetic mice

A metabolic disorder such as Type-2 Diabetes mellitus (T2DM) is a complex disease induced by genetic, environmental, and nutritional factors. The db/db mouse model, bearing a nonfunctional leptin receptor, is widely used to investigate the pathophysiology of T2DM. Fecal extracts of db/db and wild-type littermates were studied to unravel a broad spectrum of new and relevant metabolites related to T2DM as proxies of the interplay of gut microbiome and murine metabolomes. The nontargeted metabolomics approach consists of an integrated analytical concept of high-resolution mass spectrometry FT-ICR-MS, followed by UPLC-TOF-MS/MS experiments. We demonstrate that a metabolic disorder such as T2DM affects the gastrointestinal tract environment, thereby influencing different metabolic pathways and their respective metabolites in diabetic mice. Fatty acids, bile acids concerning cholic and deoxycholic acid, and steroid metabolism were highly discriminative comparing fecal meta-metabolomes of wt and db/db mice. Furthermore, sulfur-(S)-containing metabolites including N-acyl taurines were altered in diabetic mice, enabling us to focus on S-containing metabolites, especially the sulfate and taurine conjugates of bile and fatty acids. Different sulfate containing bile acids including sulfocholic acid, oxocholic acid sulfate, taurocholic acid sulfate, and cyprinol sulfate were significantly altered in diabetic mice. Moreover, we identified 12 new sulfate and taurine conjugates of hydroxylated fatty acids with significant importance in T2DM metabolism in db/db mice.

Systemic perturbations of key metabolites in diabetic rats during the evolution of diabetes studied by urine metabonomics

BACKGROUND

Elucidation of metabolic profiles during diabetes progression helps understand the pathogenesis of diabetes mellitus. In this study, urine metabonomics was used to identify time-related metabolic changes that occur during the development of diabetes mellitus and characterize the biochemical process of diabetes on a systemic, metabolic level.

METHODOLOGY/PRINCIPAL FINDINGS

Urine samples were collected from diabetic rats and age-matched controls at different time points: 1, 5, 10, and 15 weeks after diabetes modeling. (1)H nuclear magnetic resonance ((1)H NMR) spectra of the urine samples were obtained and analyzed by multivariate data analysis and quantitative statistical analysis. The metabolic patterns of diabetic groups are separated from the controls at each time point, suggesting that the metabolic profiles of diabetic rats were markedly different from the controls. Moreover, the samples from the diabetic 1-wk group are closely associated, whereas those of the diabetic 15-wk group are scattered, suggesting that the presence of various of complications contributes significantly to the pathogenesis of diabetes. Quantitative analysis indicated that urinary metabolites related to energy metabolism, tricarboxylic acid (TCA) cycle, and methylamine metabolism are involved in the evolution of diabetes.

CONCLUSIONS/SIGNIFICANCE

The results highlighted that the numbers of metabolic changes were related to diabetes progression, and the perturbed metabolites represent potential metabolic biomarkers and provide clues that can elucidate the mechanisms underlying the generation and development of diabetes as well as its complication.

The role of metabolic biomarkers in drug toxicity studies

ABSTRACT Metabolic profiling is a technique that can potentially provide more sensitive and specific biomarkers of toxicity than the current clinical measures benefiting preclinical and clinical drug studies. Both nuclear magnetic resonance (NMR) and mass spectrometry (MS) platforms have been used for metabolic profiling studies of drug toxicity. Not only can both techniques provide novel biomarker(s) of toxicity but the combination of both techniques gives a broader range of metabolites evaluated. Changes in metabolic patterns can provide insight into mechanism(s) of toxicity and help to eliminate a potentially toxic new chemical entity earlier in the developmental process. Metabolic profiling offers numerous advantages in toxicological research and screening as sample collection and preparation are relatively simple. Further, sample throughput, reproducibility, and accuracy are high. The area of drug toxicity of therapeutic compounds has already been impacted by metabolic profiling studies and will continue to be impacted as new, more specific biomarker(s) are found. In order for a biomarker or pattern of biomarkers to be accepted, it must be shown that they originate from the target tissue of interest. Metabolic profiling studies are amenable to any biofluid or tissue sample making it possible to link the changes noted in urine for instance as originating from renal injury. Additionally, the ease of sample collection makes it possible to follow a single animal or subject over time in order to determine whether and when the toxicity resolves itself. This review focuses on the advantages of metabolic profiling for drug toxicity studies.

Metabolomics in diabetes research

Diabetes represents one of the most important global health problems because it is associated with a large economic burden on the health systems of many countries. Whereas the diagnosis and treatment of manifest diabetes have been well investigated, the identification of novel pathways or early biomarkers indicative of metabolic alterations or insulin resistance related to the development of diabetes is still in progress. Over half of the type 2 diabetes patients show manifestations of diabetes-related diseases, which highlight the need for early screening markers of diabetes. During the last decade, the rapidly growing research field of metabolomics has introduced new insights into the pathology of diabetes as well as methods to predict disease onset and has revealed new biomarkers. Recent epidemiological studies first used metabolism to predict incident diabetes and revealed branched-chain and aromatic amino acids including isoleucine, leucine, valine, tyrosine and phenylalanine as highly significant predictors of future diabetes. This review summarises the current findings of metabolic research regarding diabetes in animal models and human investigations.

Application of metabolomics in traditional chinese medicine differentiation of deficiency and excess syndromes in patients with diabetes mellitus

Metabolic profiling is widely used as a probe in diagnosing diseases. In this study, the metabolic profiling of urinary carbohydrates was investigated using gas chromatography/mass spectrometry (GC/MS) and multivariate statistical analysis. The kernel-based orthogonal projections to latent structures (K-OPLS) model were established and validated to distinguish between subjects with and without diabetes mellitus (DM). The model was combined with subwindow permutation analysis (SPA) in order to extract novel biomarker information. Furthermore, the K-OPLS model visually represented the alterations in urinary carbohydrate profiles of excess and deficiency syndromes in patients with diabetes. The combination of GC/MS and K-OPLS/SPA analysis allowed the urinary carbohydrate metabolic characterization of DM patients with different traditional Chinese medicine (TCM) syndromes, including biomarkers different from non-DM patients. The method presented in this study might be a complement or an alternative to TCM syndrome research.

A metabonomic comparison of urinary changes in Zucker and GK rats

To further investigate pathogenesis and pathogenic process of type 2 diabetes mellitus (T2DM), we compared the urinary metabolic profiling of Zucker obese and Goto-kakizaki (GK) rats by NMR-based metabonomics. Principal component analysis (PCA) on urine samples of both models rats indicates markedly elevated levels of creatine/creatinine, dimethylamine, and acetoacetate, with concomitantly declined levels of citrate, 2-ketoglurarate, lactate, hippurate, and succinate compared with control rats, respectively. Simultaneously, compared with Zucker obese rats, the GK rats show decreased levels of trimethylamine, acetate, and choline, as well as increased levels of creatine/creatinine, acetoacetate, alanine, citrate, 2-ketoglutarate, succinate, lactate, and hippurate. This study demonstrates metabolic similarities between the two stages of T2DM, including reduced tricarboxylic acid (TCA) cycle and increased ketone bodies production. In addition, compared with Zucker obese rats, the GK rats have enhanced concentration of energy metabolites, which indicates energy metabolic changes produced in hyperglycemia stage more than in insulin resistance stage.

Metabonomic fingerprints of fasting plasma and spot urine reveal human pre-diabetic metabolic traits

Impaired glucose tolerance (IGT) which precedes overt type 2 diabetes (T2DM) for decades is associated with multiple metabolic alterations in insulin sensitive tissues. In an UPLC-qTOF-mass spectrometry-driven non-targeted metabonomics approach we investigated plasma as well as spot urine of 51 non-diabetic, overnight fasted individuals aiming to separate subjects with IGT from controls thereby identify pathways affected by the pre-diabetic metabolic state. We could clearly demonstrate that normal glucose tolerant (NGT) and IGT subjects clustered in two distinct groups independent of the investigated metabonome. These findings reflect considerable differences in individual metabolite fingerprints, both in plasma and urine. Pre-diabetes associated alterations in fatty acid-, tryptophan-, uric acid-, bile acid-, and lysophosphatidylcholine-metabolism, as well as the TCA cycle were identified. Of note, individuals with IGT also showed decreased levels of gut flora-associated metabolites namely hippuric acid, methylxanthine, methyluric acid, and 3-hydroxyhippuric acid. The findings of our non-targeted UPLC-qTOF-MS metabonomics analysis in plasma and spot urine of individuals with IGT vs NGT offers novel insights into the metabolic alterations occurring in the long, asymptomatic period preceding the manifestation of T2DM thereby giving prospects for new intervention targets. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-010-0203-1) contains supplementary material, which is available to authorized users.

Applications of metabolomics to understanding obesity in mouse and man

The functional genomic approach of metabolomics consists of the application of a global analytical tool to profile metabolism in a cell, tissue or organism. The most popular analytical tools include high-resolution (1)H nuclear magnetic resonance spectroscopy and mass spectrometry. Metabolomics is high throughput and relatively cheap on a per-sample basis and, hence, ideal for collecting large data sets. Biofluids are being used to follow the progression of obesity both in animal models and humans, while tissue extracts can be examined to probe the mechanisms responsible for these biofluid changes. Given these benefits and the results already produced in the field, metabolomics will play an increasing role in understanding the progression of obesity.

Metabonomics study of urine and plasma in depression and excess fatigue rats by ultra fast liquid chromatography coupled with ion trap-time of flight mass spectrometry

A novel metabonomic method based on fast liquid chromatography coupled with ion trap-time of flight mass spectrometry (UFLC/MS-IT-TOF) was applied to study the metabolic changes of plasma and urine in depression and excess fatigue rats. Principal component analysis (PCA) and partial least squares-discriminant analysis (PLS-DA) were applied for classifying the depression, excess fatigue and the control rats. Metabolites which were important for the classification in the three groups of rats were selected as potential biomarkers and identified by MS(n) information achieved from UFLC/MS-IT-TOF analysis. Spermine, propionylcarnitine, butyrylcarnitine, phenylalanine, lysophosphatidylcholine (LPC) C14:0 and LPC C18:2 were down-regulated, methyl-hippuric acid and chenodeoxycholic acid (CDCA) were up-regulated significantly in plasma of the excess fatigue rats. Spermine, leucine, propionylcarnitine, and butyrylcarnitine decreased, hippuric acid, methyl-hippuric acid, cholic acid, CDCA and LPC C16:0 increased markedly in plasma of the depression rats. Ethyl N2-acetyl-L-argininate and N-methyl-2-pyridone-5-carboxamide (2-PY) (or N-methyl-4-pyridone-3-carboxamide (4-PY)) were down-regulated, leucylproline and pantothenic acid were up-regulated remarkably both in urine of depression and excess fatigue rats. The concentration of kynurenic acid and N2-succinyl-L-ornithine was low in urine of depression rats compared with control rats. Based on the data, correlation networks for depression and excess fatigue rats revealed the abnormality of nicotinate and nicotinamide metabolism, arginine metabolism, cholesterol metabolism, tryptophan metabolism and kynurenine metabolism in depression rats, and in excess fatigue rat alterations of energy metabolism, nicotinate and nicotinamide metabolism and lecithin metabolism. Our results provide novel insights in the complex metabolic mechanisms occurring in depression and excess fatigue rats.

1H NMR metabolomics study of age profiling in children

Metabolic profiling of urine provides a fingerprint of personalized endogenous metabolite markers that correlate to a number of factors such as gender, disease, diet, toxicity, medication, and age. It is important to study these factors individually, if possible to unravel their unique contributions. In this study, age-related metabolic changes in children of age 12 years and below were analyzed by (1)H NMR spectroscopy of urine. The effect of age on the urinary metabolite profile was observed as a distinct age-dependent clustering even from the unsupervised principal component analysis. Further analysis, using partial least squares with orthogonal signal correction regression with respect to age, resulted in the identification of an age-related metabolic profile. Metabolites that correlated with age included creatinine, creatine, glycine, betaine/TMAO, citrate, succinate, and acetone. Although creatinine increased with age, all the other metabolites decreased. These results may be potentially useful in assessing the biological age (as opposed to chronological) of young humans as well as in providing a deeper understanding of the confounding factors in the application of metabolomics.

Top-down systems biology modeling of host metabotype-microbiome associations in obese rodents

Covariation in the structural composition of the gut microbiome and the spectroscopically derived metabolic phenotype (metabotype) of a rodent model for obesity were investigated using a range of multivariate statistical tools. Urine and plasma samples from three strains of 10-week-old male Zucker rats (obese (fa/fa, n=8), lean (fa/-, n=8) and lean (-/-, n=8)) were characterized via high-resolution 1H NMR spectroscopy, and in parallel, the fecal microbial composition was investigated using fluorescence in situ hydridization (FISH) and denaturing gradient gel electrophoresis (DGGE) methods. All three Zucker strains had different relative abundances of the dominant members of their intestinal microbiota (FISH), with the novel observation of a Halomonas and a Sphingomonas species being present in the (fa/fa) obese strain on the basis of DGGE data. The two functionally and phenotypically normal Zucker strains (fa/- and -/-) were readily distinguished from the (fa/fa) obese rats on the basis of their metabotypes with relatively lower urinary hippurate and creatinine, relatively higher levels of urinary isoleucine, leucine and acetate and higher plasma LDL and VLDL levels typifying the (fa/fa) obese strain. Collectively, these data suggest a conditional host genetic involvement in selection of the microbial species in each host strain, and that both lean and obese animals could have specific metabolic phenotypes that are linked to their individual microbiomes.

Global metabolic profiling and its role in systems biology to advance personalized medicine in the 21st century

Systems biology attempts to elucidate the complex interaction between genes, proteins and metabolites to provide a mechanistic understanding of cellular function and how this function is affected by disease processes, drug toxicity or drug efficacy effects. Global metabolic profiling is an important component of systems biology that can be applied in both preclinical and clinical settings for drug discovery and development, and to study disease mechanisms. The metabolic profile encodes the phenotype, which is composed of the genotype and environmental factors. The phenotypic profile can be used to make decisions about the best course of treatment for an individual patient. Understanding the combined effects of genetics and environment through a systems biology framework will enable the advancement of personalized medicine.

Advances in separation science applied to metabonomics

Metabonomics focuses on metabolite profile changes in diverse living systems caused by a biological perturbation. These metabolite signatures can be achieved with techniques such as gas chromatography, high-performance liquid chromatography (ultra-high-performance/pressure liquid chromatography and capHPLC), capillary electrophoresis, and capillary electrochromatography normally hyphenated with MS. In this review we present the latest developments of the abovementioned techniques applied in the field of metabonomics, with applications covering phytochemistry, toxicology and clinical research.

Profiling and biomarker identification in plasma from different Zucker rat strains via high mass accuracy multistage mass spectrometric analysis using liquid chromatography/mass spectrometry with a quadrupole ion trap-time of flight mass spectrometer

High mass accuracy electrospray ionisation multistage tandem mass spectrometry (MS(n)) was applied to metabolite profiling studies on plasma samples derived from two strains of rat (the Zucker (fa/fa) obese strain and the normal wild type). Using a quadrupole ion trap time-of-flight (QIT-TOF) mass spectrometer, metabolite profiling software was applied to locate components of biological significance that could account for the differences between the two strains of rat and a formula prediction software tool was used to help identify individual components. The primary factor discriminating between the two populations was the concentration of endogenous lipids. In the Zucker (fa/fa) obese strain, the dominant ion signals and MS(n) spectra were in agreement with lysoglycerophosphocholine components such as palmitoyllysophosphatidylcholine, 1-oleoylglycerophosphocholine, 1-octadecyl-sn-glycero-3-phosphocholine and 1-stearoylglycerophosphocholine and these were found in relatively higher concentrations compared to the normal wild type. Components were identified using high mass accuracy MS(n) data, formula prediction software and by agreement with published mass spectra through internet databases, rather than using a conventional approach with authentic standards. This application shows that the use of high mass accuracy electrospray ionisation MS(n) together with a software tool can be used effectively to detect and characterise unknown analytes in complex matrices, and represents a promising approach for future profiling studies.

Hydrophilic interaction and reversed-phase ultra-performance liquid chromatography TOF-MS for metabonomic analysis of Zucker rat urine

Hydrophilic interaction chromatography (HILIC) provides a complementary technique to RP methods for the retention of polar analytes for LC-MS-based metabonomic studies. Combining the advantages of both RP and HILIC separations with the efficient and rapid separations obtained using sub-2 mum particles via the recently introduced ultra-performance LC (UPLC) enables increased coverage of the metabolites present in biological samples to be achieved. Here an HILIC-UPLC-MS method was developed to provide metabolite profiles for urine samples obtained from male Zucker rats. The resulting data were compared with results obtained for the same samples by RP-UPLC-MS and demonstrated the complementary nature of the two separations with both methods enabling discrimination between the different sample types. Interestingly sample type differentiation was based on different markers.

Metabonomic study on ageing: NMR-based investigation into rat urinary metabolites and the effect of the total flavone of Epimedium

The aim of this work was to investigate the effects of ageing on rat urinary metabolites and to evaluate the anti-ageing effects of the total flavone of Epimedium (TFE). Proton nuclear magnetic resonance based metabonomic analyses was performed on urine from rats aged 4, 10, 18 and 24 months, and rats administered with TFE. By multivariate analysis, 26 characteristic resonances were found to be highly related with the age of rats, and ten of them were structurally postulated as creatinine, lactate, alanine, acetate, acetone, succinate, allantoin, methylamine, dimethylamine and trimethylamine-N-oxide; these metabolites involve creatinine metabolites, aliphatic amines metabolites and some important intermediates or end products of energy metabolism. Principal components analysis revealed that the metabolic profiles of 24-month-old rats treated with TFE closely resembled those of rats aged 18 months. In addition, most of these characteristic resonances were reset to younger levels by TFE intervention. The result suggests that TFE administration can markedly influence the ageing process and shows anti-ageing effects, which might due to the melioration of pyruyate metabolism and oxidative phosphorylation.

Piecewise multivariate modelling of sequential metabolic profiling data

Background

Modelling the time-related behaviour of biological systems is essential for understanding their dynamic responses to perturbations. In metabolic profiling studies, the sampling rate and number of sampling points are often restricted due to experimental and biological constraints.

Results

A supervised multivariate modelling approach with the objective to model the time-related variation in the data for short and sparsely sampled time-series is described. A set of piecewise Orthogonal Projections to Latent Structures (OPLS) models are estimated, describing changes between successive time points. The individual OPLS models are linear, but the piecewise combination of several models accommodates modelling and prediction of changes which are non-linear with respect to the time course. We demonstrate the method on both simulated and metabolic profiling data, illustrating how time related changes are successfully modelled and predicted.

Conclusion

The proposed method is effective for modelling and prediction of short and multivariate time series data. A key advantage of the method is model transparency, allowing easy interpretation of time-related variation in the data. The method provides a competitive complement to commonly applied multivariate methods such as OPLS and Principal Component Analysis (PCA) for modelling and analysis of short time-series data.

Metabonomics evaluations of age-related changes in the urinary compositions of male Sprague Dawley rats and effects of data normalization methods on statistical and quantitative analysis

Background

Urine from male Sprague-Dawley rats 25, 40, and 80 days old was analyzed by NMR and UPLC/MS. The effects of data normalization procedures on principal component analysis (PCA) and quantitative analysis of NMR-based metabonomics data were investigated. Additionally, the effects of age on the metabolic profiles were examined by both NMR and UPLC/MS analyses.

Results

The data normalization factor was shown to have a great impact on the statistical and quantitative results indicating the need to carefully consider how to best normalize the data within a particular study and when comparing different studies. PCA applied to the data obtained from both NMR and UPLC/MS platforms reveals similar age-related differences. NMR indicated many metabolites associated with the Krebs cycle decrease while citrate and 2-oxoglutarate, also associated with the Krebs cycle, increase in older rats.

Conclusion

This study compared four different normalization methods for the NMR-based metabonomics spectra from an age-related study. It was shown that each method of normalization has a great effect on both the statistical and quantitative analyses. Each normalization method resulted in altered relative positions of significant PCA loadings for each sample spectra but it did not alter which chemical shifts had the highest loadings. The greater the normalization factor was related to age, the greater the separation between age groups was observed in subsequent PCA analyses. The normalization factor that showed the least age dependence was total NMR intensity, which was consistent with UPLC/MS data. Normalization by total intensity attempts to make corrections due to dietary and water intake of the individual animal, which is especially useful in metabonomics evaluations of urine. Additionally, metabonomics evaluations of age-related effects showed decreased concentrations of many Krebs cycle intermediates along with increased levels of oxidized antioxidants in urine of older rats, which is consistent with current theories on aging and its association with diminishing mitochondrial function and increasing levels of reactive oxygen species. Analysis of urine by both NMR and UPLC/MS provides a comprehensive and complementary means of examining metabolic events in aging rats.

Metabonomics in diabetes research

Metabonomics has been defined as "quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification" and can provide information on disease processes, drug toxicity, and gene function. In this approach many samples of biological origin (biofluids such as urine or plasma) are analyzed using techniques that produce simultaneous detection. A variety of analytical metabolic profiling tools are used routinely, are also currently under development, and include proton nuclear magnetic resonance spectroscopy and mass spectrometry with a prior online separation step such as high-performance liquid chromatography, ultra-performance liquid chromatography, or gas chromatography. Data generated by these analytical techniques are often combined with multivariate data analysis, i.e., pattern recognition, for respectively generating and interpreting the metabolic profiles of the investigated samples. Metabonomics has gained great prominence in diabetes research within the last few years and has already been applied to understand the metabolism in a range of animal models and, more recently, attempts have been done to process complex metabolic data sets from clinical studies. A future hope for the metabonomic approach is the identification of biomarkers that are able to highlight individuals likely to suffer from diabetes and enable early diagnosis of the disease or the identification of those at risk. This review summarizes the technologies currently being used in metabonomics, as well as the studies reported related to diabetes prior to a description of the general objective of the research plan of the metabonomics part of the European Union project, Molecular Phenotyping to Accelerate Genomic Epidemiology.

A metabonomic study of strain- and age-related differences in the Zucker rat

Ultra-performance liquid chromatography (UPLC) coupled to orthogonal acceleration time-of-flight mass spectrometry (oa-TOFMS) in positive electrospray ionization mode was used to obtain metabolite profiles for urine obtained from three strains of Zucker rat. These were the Zucker lean, the Zucker (fa/fa) obese and the Zucker lean/(fa) cross. Clear age- and strain-related differences were noted with the leptin-deficient (fa/fa) obese animal showing significant differences from both the other Zucker rat strains with respect to metabolite profiles.

Metabolic profiling technologies for biomarker discovery in biomedicine and drug development

The state-of-the-art of nuclear magnetic resonance spectroscopy, mass spectrometry and statistical tools for the acquisition and evaluation of complex multidimensional spectroscopic data in metabolic profiling is reviewed in this article. The continuous evolution of the sensitivity, precision and throughput has made these technologies powerful and extremely robust tools for application in systems biology, pharmaceutical and diagnostics research. Particular emphasis is also given to the collection and storage of biological samples that are subjected to metabolite profiling. Selected examples from preclinical and clinical applications are paradigmatically shown. These illustrate the power of the profiling technologies for characterizing the metabolic phenotype of healthy, diseased and treated subjects. The complexity of disease and drug treatment is asking for an adequate response by integrated and comprehensive metabolite profiling approaches that allow the discovery of new combinations of metabolic biomarkers.

A multi-analytical platform approach to the metabonomic analysis of plasma from normal and zucker (fa/fa) obese rats

Plasma obtained from 20 week old normal Wistar-derived and Zucker (fa/fa) rats was analysed using a number of different analytical methodologies to obtain global metabolite profiles as part of metabonomic investigations of animal models of diabetes. Samples were analysed without sample pre-treatment using 1H NMR spectroscopy, after acetonitrile solvent protein precipitation by ultra-performance liquid chromatography-MS (UPLC-MS) and after acetonitrile protein precipitation and derivatisation for capillary gas chromatography-MS (GC-MS). Subsequent data analysis using principal components analysis revealed that all three analytical platforms readily detected differences between the plasma metabolite profiles of the two strains of rat. There was only limited overlap between the metabolites detected by the different methodologies and the combination of all three methods of metabolite profiling therefore provided a much more comprehensive profile than would have been provided by their use individually.