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ObjectiveThe composition and metabolic function of the gut microbiome in the elite athlete differs from that of non-athletes. However, short-term fitness improvement in the sedentary adult does not replicate the microbiome characteristics seen in the athlete. Whether sustained fitness improvement over a prolonged period can lead to pronounced and beneficial alteration in the gut microbiome is unknown. The objective was to explore this possibility.MethodsThis study used a repeated-measures, case-study approach to explore changes in the gut microbiome of two unfit volunteers undertaking progressive exercise training over a 6-month period. Training was to culminate in the completion of a marathon or Olympic-distance triathlon. The volunteers were sampled every two weeks for six months and microbiome, metabolome, diet, body composition, and cardiorespiratory fitness data were recorded.ResultsBoth participants completed their respective goals with improved body composition and fitness parameters over the training period. Increases in α-diversity of the gut microbiota occurred with sustained training and fluctuations occurred in response to training events (e.g., injury, illness and training peaks). Participants’ fat mass and BMI reduced during the study and was significantly associated with increased urinary measurements of N-methyl nicotinate (P value < 0.001) and hippurate (P value < 0.05), and decreased phenylacetylglutamine (P value < 0.05).ConclusionThese results suggest that sustained fitness improvements result in alterations to gut microbiota and physiologically-relevant metabolites. This study provides longitudinal analysis of the response of the gut microbiome to real-world events during progressive fitness training, including intercurrent illness and injury.

Prior investigation has suggested a positive association between increased colonic propionate production and circulating odd-chain fatty acids [(OCFAs; pentadecanoic acid (C15:0), heptadecanoic acid (C17:0)]. As the major source of propionate in humans is the microbial fermentation of dietary fiber, OCFAs have been proposed as candidate biomarkers of dietary fiber. The objective of this study is to critically assess the plausibility, robustness, reliability, dose-response, time-response aspects of OCFAs as potential biomarkers of fermentable fibers in two independent studies using a validated analytical method. OCFAs were first assessed in a fiber supplementation study, where 21 participants received 10g dietary fiber supplementation for 7 days with blood samples collected on the final day at a 420 minute study visit. OCFAs were then assessed in a highly controlled inpatient setting, which 19 participants consumed a high fiber (45.1g/day) and a low fiber diet (13.6g/day) for 4 days. Collectively in both studies, dietary intakes of fiber as fiber supplementations or having consumed a high fiber diet did not increase circulating levels of OCFAs. The dose and temporal relations were not observed. Current study has generated new insight on the utility of OCFAs as fiber biomarkers and highlighted the importance of critical assessment of candidate dietary biomarkers before application.

NMR is a mature technique that is well established and adopted in a wide range of research facilities from laboratories to hospitals. This accounts for large amounts of valuable experimental data that may be readily exported into a standard and open format. Yet the publication of these data faces an important issue: Raw data are not made available; instead, the information is slimed down into a string of characters (the list of peaks). Although historical limitations of technology explain this practice, it is not acceptable in the era of Internet. The idea of modernizing the strategy for sharing NMR data is not new, and some repositories exist, but sharing raw data is still not an established practice. Here, we present a powerful toolbox built on recent technologies that runs inside the browser and provides a means to store, share, analyse, and interact with original NMR data. Stored spectra can be streamlined into the publication pipeline, to improve the revision process for instance. The set of tools is still basic but is intended to be extended. The project is open source under the Massachusetts Institute of Technology (MIT) licence.

Aim Gut microbial dysbiosis is implicated in the pathogenesis of non-alcoholic steatohepatitis (NASH). We investigated downstream effects of gut microbiota modulation on markers of hepatic inflammation, steatosis, and hepatic and peripheral insulin sensitivity in patients with NASH using rifaximin therapy. Methods Patients with biopsy-proven NASH and elevated aminotransferase values were included in this open-label pilot study, all receiving 6 weeks rifaximin 400 mg twice daily, followed by a 6-week observation period. The primary endpoint was change in alanine aminotransferase (ALT) after 6 weeks of rifaximin. Secondary endpoints were change in hepatic lipid content and insulin sensitivity measured with a hyperinsulinemic–euglycemic clamp. Results Fifteen patients (13 men and 2 women) with a median (range) age of 46 (32–63) years were included. Seven had diabetes on oral hypoglycemic medications and 8 had no diabetes. After 6 weeks of therapy, no differences were seen in ALT (55 [33–191] vs. 63 [41–218] IU/L, P = 0.41), peripheral glucose uptake (28.9 [19.4–48.3] to 25.5 [17.7–47.9] μmol/kg/min, P = 0.30), hepatic insulin sensitivity (35.2 [15.3–51.7]% vs. 30.0 [10.8–50.5]%, P = 0.47), or hepatic lipid content (21.6 [2.2–46.2]% vs. 24.8 [1.7–59.3]%, P = 0.59) before and after rifaximin treatment. After 12 weeks from baseline, serum ALT increased to 83 (30–217) IU/L, P = 0.02. There was a significant increase in the homeostasis model assessment–estimated insulin resistance index (P = 0.05). The urinary metabolic profile indicated a significant reduction in urinary hippurate with treatment, which reverted to baseline after cessation of rifaximin, although there was no consistent difference in relative abundance of fecal microbiota with treatment. Conclusion These data do not indicate a beneficial effect of rifaximin in patients with NASH.

Summary Obesity is a major health concern in the Middle East and the incidence is rising in all sections of the population. Efforts to control obesity through diet and lifestyle interventions, and by surgical means, have had limited effect, and the gene–environment interactions underpinning the development of obesity and related pathologies such as metabolic syndrome, cardiovascular disease and certain cancers are poorly defined. Lifestyle, genetics, inflammation and the interaction between the intestinal bacteria and host metabolism have all been implicated in creating an obesogenic environment. We summarize the role of metabolic and microbial phenotyping in understanding the aetiopathogenesis of obesity and in characterizing the metabolic responses to surgical and non-surgical interventions, and explore the potential for clinical translation of this approach.

REASONS FOR PERFORMING STUDY: Metabonomics is emerging as a powerful tool for disease screening and investigating mammalian metabolism. This study aims to create a metabolic framework by producing a preliminary reference guide for the normal equine metabolic milieu. OBJECTIVES: To metabolically profile plasma, urine and faecal water from healthy racehorses using high resolution (1) H-nuclear magnetic resonance (NMR) spectroscopy and to provide a list of dominant metabolites present in each biofluid for the benefit of future research in this area. STUDY DESIGN: This study was performed using 7 Thoroughbreds in race training at a single time point. Urine and faecal samples were collected noninvasively and plasma was obtained from samples taken for routine clinical chemistry purposes. METHODS: Biofluids were analysed using (1) H-NMR spectroscopy. Metabolite assignment was achieved via a range of one- and 2-dimensional experiments. RESULTS: A total of 102 metabolites were assigned across the 3 biological matrices. A core metabonome of 14 metabolites was ubiquitous across all biofluids. All biological matrices provided a unique window on different aspects of systematic metabolism. Urine was the most populated metabolite matrix with 65 identified metabolites, 39 of which were unique to this biological compartment. A number of these were related to gut microbial host cometabolism. Faecal samples were the most metabolically variable between animals; acetate was responsible for the majority (28%) of this variation. Short-chain fatty acids were the predominant features identified within this biofluid by (1) H-NMR spectroscopy. CONCLUSIONS: Metabonomics provides a platform for investigating complex and dynamic interactions between the host and its consortium of gut microbes and has the potential to uncover markers for health and disease in a variety of biofluids. Inherent variation in faecal extracts along with the relative abundance of microbial-mammalian metabolites in urine and invasive nature of plasma sampling, infers that urine is the most appropriate biofluid for the purposes of metabonomic analysis.

Background Biomarkers of Alzheimer’s disease (AD) pathology and progression have now been identified across various modalities. The aims of the two studies presented (ANM-MMB and EMIF-AD biomarker discovery) are to discover and replicate previously identified biomarkers of disease pathology and progression, and moreover to determine whether a multimodal biomarker signature may add value in comparison to a biomarker of a single modality. Methods The ANM-MMB cohort is comprised of 718 AD, MCI converters and non-converters, and control subjects selected from the AddNeuroMed, Alzheimer’s research trust and Dementia case register cohorts. Cognitive measures, serum and urine metabolomics, structural MRI, genomics, whole blood transcriptomics and plasma proteomics data was available. The EMIF-AD biomarker discovery cohort consists of 1221 AD, MCI and control subjects, selected from the EMIF catalogue. All subjects had existing amyloid measures (CSF Aβ or amyloid-PET), structural MRI and clinical data, and furthermore plasma proteomics (targeted and untargeted), CSF proteomics (targeted), metabolomics, genomics and epigenetics data were generated. For both studies univariate and multivariate statistics were utilised to identify candidate biomarkers of AD pathology (neurodegeneration and/or brain amyloid burden), rates of cognitive decline, and MCI progression to dementia. pQTL-eQTL-mQTL analyses, network/pathway analysis, and multimodal classifiers were employed to detect multimodal signatures. Results Initial analyses indicate that in the ANM-MMB study a serum and urine derived 15 metabolite classifier predicts MCI progression to AD with 72% accuracy, and the biological significance of the metabolites included in the biomarker panel was identified. Further analyses will examine whether a multimodal classifier is able to predict with even greater accuracy. We will then seek to replicate this in the EMIF-AD biomarker discovery study. Further analyses will also examine single and multimodal biomarker classifiers of other endophenotypes. Conclusions These two studies could be used to identify novel and replicate previously identified single modality biomarker findings. Furthermore the impact of combining the additional modalities with these findings will be discussed. Computational and technical challenges encountered and the bioinformatics pipeline devised in the multimodal analysis of the ANM-MMB cohort will be used to inform the analysis pipeline of the EMIF-AD biomarker discovery study as a replication.

Identifying dietary tools that prevent disordered insulin secretion from pancreatic β‐cells is an attractive strategy to combat the increasing prevalence of type 2 diabetes. Dietary resistant starch has been linked to improvements in the function of β‐cells, possibly via increased colonic fermentation and production of short‐chain fatty acids (SCFAs). Increasing the resistant starch content of commonly consumed foods could therefore maintain glucose homeostasis at the population level. As part of Biotechnology and Biological Sciences Research Council (BBSRC) Diet and Health Research Industry Club (DRINC) initiative, variants of Pisum sativum L. (pea) are being investigated to identify the features of pea starch that make it resistant to digestion and available for colonic fermentation and SCFA production. Parallel in vitro and in vivo studies are being conducted using both whole pea seeds and pea flour to facilitate a better understanding of how cells in the pea cotyledons are affected by processing and, in turn, how this influences starch digestibility. Trials in human volunteers are being used to monitor a full spectrum of short‐ and long‐term physiological responses relevant to pancreatic β‐cell function and glucose homeostasis. This project is providing new insights into variants of crops that are associated with the specific types of resistant starch that provide the best protection against defects in insulin secretion and function.

Objective: Obesity often clusters with other major cardiovascular disease risk factors, yet a subset of the obese appears to be protected from these risks. Two obesity phenotypes are described, (i) “metabolically healthy” obese, broadly defined as body mass index (BMI) ≥ 30 kg/m2 and favorable levels of blood pressure, lipids, and glucose; and (ii) “at risk” obese, BMI ≥ 30 with unfavorable levels of these risk factors. More than 30% of obese American adults are metabolically healthy. Diet and activity determinants of obesity phenotypes are unclear. We hypothesized that metabolically healthy obese have more favorable behavioral factors, including less adverse diet composition and higher activity levels than at risk obese in the multi-ethnic group of 775 obese American adults ages 40-59 years from the International Population Study on Macro/Micronutrients and Blood Pressure (INTERMAP) cohort. Design and Methods: In gender-stratified analyses, mean values for diet composition and activity behavior variables, adjusted for age, race, and education, were compared between metabolically healthy and at risk obese. Results: Nearly one in five (149/775 or 19%) of obese American INTERMAP participants were classified as metabolically healthy obese. Diet composition and most activity behaviors were similar between obesity phenotypes, although metabolically healthy obese women reported higher sleep duration than at risk obese women. Conclusions: These results do not support hypotheses that diet composition and/or physical activity account for the absence of cardiometabolic abnormalities in metabolically healthy obese.

The global prevalence of type 2 diabetes mellitus and impaired glucose metabolism continues to rise in conjunction with the pandemic of obesity. The metabolic Roux-en-Y gastric bypass operation offers the successful resolution of diabetes in addition to sustained weight loss and excellent long-term outcomes in morbidly obese individuals. The procedure consists of the physiological BRAVE effects: (i) Bile flow alteration; (ii) Reduction of gastric size; (iii) Anatomical gut rearrangement and altered flow of nutrients; (iv) Vagal manipulation and (v) Enteric gut hormone modulation. This operation provides anti-diabetic effects through decreasing insulin resistance and increasing the efficiency of insulin secretion. These metabolic outcomes are achieved through weight-independent and weight-dependent mechanisms. These include the foregut, midgut and hindgut mechanisms, decreased inflammation, fat, adipokine and bile metabolism, metabolic modulation, shifts in gut microbial composition and intestinal gluconeogenesis. In a small minority of patients, gastric bypass results in hyperinsulinaemic hypoglycaemia that may lead to nesidioblastosis (pancreatic beta-cell hypertrophy with islet hyperplasia). Elucidating the precise metabolic mechanisms of diabetes resolution and hyperinsulinaemia after surgery can lead to improved operations and disease-specific procedures including 'diabetes surgery'. It can also improve our understanding of diabetes pathogenesis that may provide novel strategies for the management of metabolic syndrome and impaired glucose metabolism.

Introduction – High salinity, caused by either natural (e.g. climatic changes) or anthropic factors (e.g. agriculture), is a widespread environmental stressor that can affect development and growth of salt-sensitive plants, leading to water deficit, the inhibition of intake of essential ions and metabolic disorders. Objective – The application of an NMR-based metabolic profiling approach to the investigation of saline-induced stress in Maize plants is presented. Methodology – Zea Maize seedlings were grown in either 0, 50 or 150 mM saline solution. Plants were harvested after 2, 4 and 6 days (n = 5 per class and time point) and 1H NMR spectroscopy was performed separately on shoot and root extracts. Spectral data were analysed and interpreted using multivariate statistical analyses. Results – A distinct effect of time/growth was observed for the control group with relatively higher concentrations of acetoacetate at day 2 and increased levels of alanine at days 4 and 6 in root extracts, whereas concentration of alanine was positively correlated with the shoot extracts harvested at day 2 and trans-aconitic acid increased at days 4 and 6. A clear dose-dependent effect, superimposed on the growth effect, was observed for saline treated shoot and root extracts. This was correlated with increased levels of alanine, glutamate, asparagine, glycine-betaine and sucrose and decreased levels of malic acid, trans-aconitic acid and glucose in shoots. Correlation with salt-load shown in roots included elevated levels of alanine, γ-amino-N-butyric acid, malic acid, succinate and sucrose and depleted levels of acetoacetate and glucose. Conclusions – The metabolic effect of high salinity was predominantly consistent with osmotic stress as reported for other plant species and was found to be stronger in the shoots than the roots. Using multivariate data analysis it is possible to investigate the effects of more than one environmental stressor simultaneously. Copyright © 2010 John Wiley & Sons, Ltd.

Metabonomics is a key element in systems biology, and with current analytical methods, generates vast amounts of quantitative or qualitative metabolic data. Understanding of the global function of the living organism can be achieved by integration of ‘omics’ approaches including metabonomics, genomics, transcriptomics and proteomics, increasing the complexity of the full data sets. Multivariate statistical approaches are well suited to extract the characterizing metabolic information associated with each level of dynamic process. In this review, we discuss techniques that have evolved from principal component analysis and partial least squares (PLS) methods with a focus on improved interpretation and modeling with respect to biomarker recovery and data visualization in the context of metabonomic applications. Visualization is of paramount importance to investigate complex metabolic signatures, the power and potential of which is illustrated with key papers. Recent improvements based on the removal of orthogonal variation are discussed in terms of interpretation enhancement, and are supported by relevant applications. Flexibility of PLS methods in general and of O-PLS in particular allows implementation of derivative methods such as O2-PLS, O-PLS-variance components, nonlinear methods, and batch modeling to improve analysis of complex data sets, which facilitates extraction of information related to subtle biological processes. These approaches can be used to address issues present in complex multi-factorial data sets. Thus, we highlight the key advantages and limitations of the different latent variable applications for top-down systems biology and assess the differences between the methods available. Copyright © 2010 John Wiley & Sons, Ltd.

The eff ects of sample preparation and chromatographic method diff erences on the classifi cation and recovery of metabolic biomarkers from UPLC-MS measurements on urine samples of humans exposed to diff erent dietary interventions have been investigated. Eight volunteers consumed three high-fat meals (rich in saturated, monounsaturated and polyunsatu- rated fatty acids, respectively) in randomized order with a washout period in between. For each participant, urine samples were obtained prior to and at three timed intervals after each meal. Samples were processed either by dilution (1 : 4) or by liquid-liquid extraction and then run under two diff erent gradient conditions. For each analysis method, a total of 96 observa- tions (eight participants, four time points, three diets) were measured. The total ion count chromatograms were analyzed using partial-least-squares discriminant analysis. All three dietary classes could be discriminated irrespective of sample prepa- ration and chromatographic method. However, the main discriminating metabolites varied according to sample preparation, indicating that sample treatment and chromatographic conditions infl uence the ability to extract biomolecular information. Diluted samples showed higher m/z compounds (ca 400 u) while liquid-liquid extraction samples showed low m/z at the same retention time span. Optimized methods for metabolite identifi cation (e.g. organic acids) were statistically inferior to global screening for mixed compound identifi cation, confi rming that multiple compound class-based metabolic profi les are likely to give superior metabonomic (diagnostic) classifi cation, although great care has to be taken in the interpretation in relation to matrix eff ects. Copyright © 2009 John Wiley & Sons, Ltd.

The time-related metabolic effects of 1-cyano-2-hydroxy-3-butene (CHB, crambene), a naturally occurring nitrile and experimental model toxin causing exocrine pancreatitis, have been investigated in rats using high-resolution NMR spectroscopy of urine and serum in combination with pattern recognition analysis. Rats were administered CHB subcutaneously in two doses, 15 mg/kg dose (n = 10) and 150 mg/kg (n = 10), and conventional histopathology and clinical chemistry assessments were performed. Urine samples were collected at − 16 and 0, 8, 24, 48, 72, 96, 120, 144 and 168 h postdosing and serum samples were collected at 48 and 168 h postdosing; these were analyzed using a range of 1D and 2D NMR spectroscopic methods. The metabolic profile perturbations seen throughout the time-course of the study are described, and the application of the spectral correlation technique Statistical TOtal Correlation SpectroscopY (STOCSY) to detect both structural and novel toxicological connectivities between xenobiotic and endogenous metabolite signals is illustrated for the first time. As a result, it is suggested that the STOCSY approach may be of wider application in the identification of toxic versus nontoxic metabolites in drug metabolism studies. Copyright © 2009 John Wiley & Sons, Ltd.

This minireview is based on a lecture given at the First Maga Circe Conference on metabolomics held at Sabaudia, Italy, in March 2006 in which the analytical and statistical techniques used in metabonomics, efforts at standardization and some of the major applications to pharmaceutical research and development are reviewed. Metabonomics involves the determination of multiple metabolites simultaneously in biofluids, tissues and tissue extracts. Applications to preclinical drug safety studies are illustrated by the Consortium for Metabonomic Toxicology, a collaboration involving several major pharmaceutical companies. This consortium was able, through the measurement of a dataset of NMR spectra of rodent urine and serum samples, to build a predictive expert system for liver and kidney toxicity. A secondary benefit was the elucidation of the endogenous biochemicals responsible for the classification. The use of metabonomics in disease diagnosis and therapy monitoring is discussed with an exemplification from coronary artery disease, and the concept of pharmaco-metabonomics as a way of predicting an individual's response to treatment is exemplified. Finally, some advantages and perceived difficulties of the metabonomics approach are summarized.

Strategies such as genomics, proteomics and metabonomics are being applied with increasing frequency in the pharmaceutical industry. For each of these approaches, toxicological response can be measured by terms of deviation from control or baseline status. However, in order to accurately define drug-induced response, it is necessary to characterize the normal degree of physiological variation in the absence of stimuli. Here, 1H NMR spectroscopic-based analyses of the metabolic composition of urine in experimental animals under various normal physiological conditions are reviewed. In particular, the effects of inter-animal and diurnal variation, gender, age, diet, species, strain, hormonal status and stress on the biochemical composition of urine are explored. Pattern recognition methods facilitate the comparison of urine NMR spectra over a given time-course, enabling the establishment of changes in profile and highlighting the dynamic metabolic status of an organism. Thus metabonomic approaches based on information-rich spectroscopic data sets can be used to evaluate normal physiological variation and for investigation of drug safety issues.

Multivariate statistical batch processing (BP) analysis of 1H nuclear magnetic resonance (NMR) urine spectra was employed to establish time-dependent metabolic variations in animals treated with th ...

The application of high-field 1H NMR spectroscopy to the analysis of biological fluids has proved to be a valuable approach to toxicological screening. Coupled with data reduction and chemometric analyses, this technology has a high capacity for elucidating relevant metabolic information pertaining to the nature and mechanism of toxic processes in an organism. This approach is encapsulated in the concept of metabonomics, which is defined as ‘the quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification’, and can be regarded as complementary to studies of the genome (genomics) and the proteins in an organism (proteomics). Here the metabonomics approach to drug toxicity evaluation is exemplified using 1H NMR spectroscopy to investigate the biochemical perturbations in urine after dosing Fischer rats with the cationic, amphiphilic drugs chloroquine, amiodarone and DMP 777, a neutrophil elastase inhibitor. These drugs are known to induce phospholipidosis, characterized by lysosomal lamellar body and drug accumulation. Using a metabonomic approach, combinations of specific urinary biomarkers were identified for each compound, together with a putative general marker of phospholipidosis, phenylacetylglycine. Furthermore, in the case of chloroquine, clear evidence of hepatotoxicity was determined. Copyright © 2001 John Wiley & Sons, Ltd.

The technique of magic angle spinning (MAS) high resolution 1H NMR spectroscopy applied to intact tissues provides excellent peak resolution and thus much biochemical information. The use of computer-based pattern recognition techniques to classify human renal cortex tissue samples as normal or tumour based on their 1H MAS NMR spectra has been investigated. In this preliminary study of 22 paired control and tumour samples, exploratory data analysis using principal components based on NMR spectral intensities showed clear separation of the two classes. Furthermore, using the supervised method of linear discriminant analysis, based on individual data point intensities or on integrated spectral regions, it was possible to distinguish between the normal and tumour kidney cortex tissue with 100% accuracy, including a single example of a metastatic tumour from a primary lung carcinoma. A tumour sample from the collecting duct of the kidney showed a different NMR spectral profile, and pattern recognition indicated that this sample did not classify with the cortical tumours. © 2000 John Wiley & Sons, Ltd.

High-resolution magic angle spinning (MAS) (1)H NMR spectra of small samples (ca. 8 mg) of intact rat liver are reported for the first time. One dimensional spectra reveal a number of large well-resolved NMR signals mainly from low to medium molecular weight compounds (generally 4) linked glucose units with either alpha(1-->4) units adjacent or alpha(1-->6) linked branches could be resolved in a high-resolution (1)H NMR experiment giving direct in situ information on the ratio of alpha(1-->4) to alpha(1-->6) units. This indicates that despite the relatively high MW (>1,000,000 Daltons) there is considerable segmental motion in the glycogen molecules giving long (1)H T(2) relaxation times. Magn Reson Med 44:201-207, 2000.

NMR spectroscopy of biofluids provides a wealth of information on the endogenous metabolic processes in an organism. Details of the various types of biofluid and the types of NMR experiment which are useful are given. The features of biofluid NMR spectra are described and practical details of spectral acquisition are also presented. However, the spectra are very complex and many resonances have not been assigned. Therefore, in order to focus on significant differences between a set of spectra from control organisms and from abnormals (e.g., humans with diseases or animals in toxic situations), recourse is made to pattern recognition or chemometric methods. This is exemplifed using NMR spectra of a number of different biofluids such as urine, blood plasma, and cerebrospinal fluid. This approach is encapsulated in the concept of metabonomics, a subject which can be regarded as complementary to studies of the genome (genomics) and the proteins in an organism (proteomics). Metabonomics is defined as "the quantitative measurement of the multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification."

A single dose of puromycin aminonucleoside (PAN) given parenterally to rats induces ultrastructural glomerular changes and a nephrotic syndrome similar in many respects to human minimal change nephropathy. The exact aetiologies of both the human and the experimental syndromes are unknown, and are probably multifactorial. However, among the observed consequences in humans and rats is increased plasma protein excretion in urine, beginning in the latter typically 3-6 days after PAN administration. In view of this, two-dimensional polyacrylamide gel electrophoresis (2-D PAGE) has been used to profile urinary proteins during PAN-induced nephrotoxicity and subsequent recovery in the rat. In addition, urinary high performance liquid chromatography (HPLC) profiles and high resolution proton nuclear magnetic resonance (NMR) spectroscopy has been utilised to simultaneously detect toxin-induced changes in the relative concentrations of a number of metabolites. The proteomic approach, in conjunction with these other techniques, has the potential to provide significantly more mechanistic information than is provided readily by traditional clinical chemistry.

High-resolution magic angle spinning 1H NMR (MAS-NMR) spectroscopy was used to investigate the biochemical composition of normal renal cortex and renal papilla samples from rats, and results were compared with those from conventional 1H NMR analysis of protein-free tissue extracts. 1H MAS NMR spectra of samples obtained from inner and outer cortex were found to be broadly similar in terms of metabolite profile, and intra- and inter-animal variability was small. However, the MAS NMR spectra from renal papilla samples were qualitatively and quantitatively different from those obtained from cortex. High levels of free amino acids and several organic acids were detected in the cortex, together with choline, glucose, and trimethylamine-N-oxide. The dominant metabolite resonances observed in papillary tissue were from glycerophosphocholine (GPC), betaine, myo-inositol, and sorbitol. On increasing the magic angle spinning rate from 4,200 to 12,000 Hz, the lipid MAS 1H NMR signal profile remained largely unchanged in papillary tissue, whereas "new" resonances from triglycerides appeared in the spectra of cortical tissue, this effect being reversible on returning the spinning rate to 4,200 Hz. Further investigation into the behavior of the lipid components under different spinning rates suggested that the lipids in the cortex were present in more motionally constrained environments than those in the papilla. 1H MAS NMR spectra of tissues are of value both in interrogation of the biochemical composition of whole tissue, and in obtaining information on the mobility and compartmentalization of certain metabolites.

Pattern recognition approaches were developed and applied to the classification of 600 MHz 1 H NMR spectra of urine from rats dosed with compounds that induced organ-specific damage in either the liver or kidney. Male rats were separated into groups (n = 5) and each treated with one of the following compounds; adriamycin, allyl alcohol, 2-bromoethanamine hydrobromide, hexachlorobutadiene, hydrazine, lead acetate, mercury II chloride, puromycin aminonucleoside, sodium chromate, thioacetamide, 1,1,2-trichloro-3,3,3-trifluoro-1-propene or dose vehicle. Urine samples were collected over a 7 day time-course and analysed using 600 MHz 1 H NMR spectroscopy. Each NMR spectrum was data-reduced to provide 256 intensity-related descriptors of the spectra. Data corresponding to the periods 8-24 h, 24-32 h and 32-56 h post-dose were first analysed using principal components analysis (PCA). In addition, samples obtained 120-144 h following the administration of adriamycin and puromycin were included in the analysis in order to compensate for the late onset of glomerular toxicity. Having established that toxin-related clustering behaviour could be detected in the first three principal components (PCs), three-quarters of the data were used to construct a soft independent modelling of class analogy (SIMCA) model. The remainder of the data were used as a test set of the model. Only three out of 61 samples in the test set were misclassified. Finally as a further test of the model, data from the 1 H NMR spectra of urine from rats that had been treated with uranyl nitrate were used. Successful prediction of the toxicity type of the compound was achieved based on NMR urinalysis data confirming the robust nature of the derived model. © 1998 John Wiley & Sons, Ltd.

A role for the intestinal microbiota is routinely cited as a potential aetiological factor in colorectal cancer initiation and progression. As the majority of bacteria in the gut are refractory to culture we investigated this ecosystem in subjects with colorectal cancer and with adenomatous polyposis who are at high risk of developing colorectal cancer, using culture-independent methods. Twenty colorectal cancer and 20 polypectomized volunteers were chosen for this analysis. An exploration of the diversity and temporal stability of the dominant bacteria and several bacterial subgroups was undertaken using 16S rRNA gene denaturing gradient gel electrophoresis and ribosomal intergenic spacer analysis (RISA). Metabonomic analysis of the distal gut microbiota's environment was also undertaken. A significantly reduced temporal stability and increased diversity for the microbiota of subjects with colorectal cancer and polyposis was evident. A significantly increased diversity of the Clostridium leptum and C. coccoides subgroups was also noted for both disease groups. A clear division in the metabonome was observed for the colorectal cancer and polypectomized subjects compared with control volunteers. The intestinal microbiota and their metabolites are significantly altered in both colorectal cancer and polypectomized subjects compared with controls.