Improved Spatial Resolution of Metabolites in Tissue Biopsies Using High-Resolution Magic-Angle-Spinning Slice Localization NMR Spectroscopy.

High-resolution magic-angle-spinning 1H NMR spectroscopy (HR-MAS NMR) is a well-established technique for assessing the biochemical composition of intact tissue samples. In this study, we utilized a method based on HR-MAS NMR spectroscopy with slice localization (SLS) to achieve spatial resolution of metabolites. The obtained 7 slice spectra from each of the model samples (i.e., chicken thigh muscle with skin and murine renal biopsy including medulla (M) and cortex (C)) showed distinct metabolite compositions. Furthermore, we analyzed previously acquired 1H HR-MAS NMR spectra of separated cortex and medulla samples using multivariate statistical methods. Concentrations of glycerophosphocholine (GPC) were found to be significantly higher in the renal medulla compared to the cortex. Using GPC as a biomarker, we identified the tissue slices that were predominantly the cortex or medulla. This study demonstrates that HR-MAS SLS combined with multivariate statistics has the potential for identifying tissue heterogeneity and detailed biochemical characterization of complex tissue samples.

NMR and MS urinary metabolic phenotyping in kidney diseases is fit-for-purpose in the presence of a protease inhibitor.

Nephrotic syndrome with idiopathic membranous nephropathy as a major contributor, is characterized by proteinuria, hypoalbuminemia and oedema. Diagnosis is based on renal biopsy and the condition is treated using immunosuppressive drugs; however nephrotic syndrome treatment efficacy varies among patients. Multi-omic urine analyses can discover new markers of nephrotic syndrome that can be used to develop personalized treatments. For proteomics, a protease inhibitor (PI) is sometimes added at sample collection to conserve proteins but its impact on urine metabolic phenotyping needs to be evaluated. Urine from controls (n = 4) and idiopathic membranous nephropathy (iMN) patients (n = 6) were collected with and without PI addition and analysed using 1H NMR spectroscopy and UPLC-MS. PI-related data features were observed in the 1H NMR spectra but their removal followed by a median fold change normalisation, eliminated the PI contribution. PI-related metabolites in UPLC-MS data had limited effect on metabolic patterns specific to iMN. When using an appropriate data processing pipeline, PI-containing urine samples are appropriate for 1H NMR and MS metabolic profiling of patients with nephrotic syndrome.

Integrated Analytical and Statistical Two-Dimensional Spectroscopy Strategy for Metabolite Identification: Application to Dietary Biomarkers.

A major purpose of exploratory metabolic profiling is for the identification of molecular species that are statistically associated with specific biological or medical outcomes; unfortunately, the structure elucidation process of unknowns is often a major bottleneck in this process. We present here new holistic strategies that combine different statistical spectroscopic and analytical techniques to improve and simplify the process of metabolite identification. We exemplify these strategies using study data collected as part of a dietary intervention to improve health and which elicits a relatively subtle suite of changes from complex molecular profiles. We identify three new dietary biomarkers related to the consumption of peas (N-methyl nicotinic acid), apples (rhamnitol), and onions (N-acetyl-S-(1Z)-propenyl-cysteine-sulfoxide) that can be used to enhance dietary assessment and assess adherence to diet. As part of the strategy, we introduce a new probabilistic statistical spectroscopy tool, RED-STORM (Resolution EnhanceD SubseT Optimization by Reference Matching), that uses 2D J-resolved 1H NMR spectra for enhanced information recovery using the Bayesian paradigm to extract a subset of spectra with similar spectral signatures to a reference. RED-STORM provided new information for subsequent experiments (e.g., 2D-NMR spectroscopy, solid-phase extraction, liquid chromatography prefaced mass spectrometry) used to ultimately identify an unknown compound. In summary, we illustrate the benefit of acquiring J-resolved experiments alongside conventional 1D 1H NMR as part of routine metabolic profiling in large data sets and show that application of complementary statistical and analytical techniques for the identification of unknown metabolites can be used to save valuable time and resources.

Multiplatform serum metabolic phenotyping combined with pathway mapping to identify biochemical differences in smokers.

AIM: Determining perturbed biochemical functions associated with tobacco smoking should be helpful for establishing causal relationships between exposure and adverse events. RESULTS: A multiplatform comparison of serum of smokers (n = 55) and never-smokers (n = 57) using nuclear magnetic resonance spectroscopy, UPLC-MS and statistical modeling revealed clustering of the classes, distinguished by metabolic biomarkers. The identified metabolites were subjected to metabolic pathway enrichment, modeling adverse biological events using available databases. Perturbation of metabolites involved in chronic obstructive pulmonary disease, cardiovascular diseases and cancer were identified and discussed. CONCLUSION: Combining multiplatform metabolic phenotyping with knowledge-based mapping gives mechanistic insights into disease development, which can be applied to next-generation tobacco and nicotine products for comparative risk assessment.

Application of CE-MS to a metabonomics study of human urine from cigarette smokers and non-smokers.

BACKGROUND: Novel biomarkers of exposure and early adverse effects are needed for comparative studies of combustible and non-combustible tobacco products for regulatory authority evaluation. Metabolic biomarkers reflect both gene and environmental effects. RESULTS: CE-MS has been applied to human urine samples from non-smokers and smokers of cigarettes at two tar levels. Validated chemometric models were able to separate smokers from non-smokers, with discrimination mainly based on the presence of nicotine metabolites. With these removed, it still proved possible to discriminate smokers from non-smokers with models now based on endogenous metabolites. The biochemical relevance of these biomarkers is discussed. CONCLUSION: This proof-of-principle metabonomics study illustrates the potential of CE-MS to discover novel biomarkers in urine from tobacco users.

The emergent role of metabolic phenotyping in dynamic patient stratification.

The role that metabolic phenotyping can increasingly play in patient stratification and personalised medicine is discussed. The background to the general approach, comprehensive and simultaneous analysis of small-molecule metabolites in biofluids, tissues and tissue extracts combined with suitable multivariate statistical models, is summarised. The main techniques used (NMR and mass spectrometry) are cited, and the implementation of dedicated phenome centres is explained. Finally, the advantages and limitations, opportunities and drawbacks of the approach are discussed.

Metabolic phenotyping in clinical and surgical environments.

Metabolic phenotyping involves the comprehensive analysis of biological fluids or tissue samples. This analysis allows biochemical classification of a person's physiological or pathological states that relate to disease diagnosis or prognosis at the individual level and to disease risk factors at the population level. These approaches are currently being implemented in hospital environments and in regional phenotyping centres worldwide. The ultimate aim of such work is to generate information on patient biology using techniques such as patient stratification to better inform clinicians on factors that will enhance diagnosis or the choice of therapy. There have been many reports of direct applications of metabolic phenotyping in a clinical setting.

Evaluation of high resolution magic-angle coil spinning NMR spectroscopy for metabolic profiling of nanoliter tissue biopsies.

High-resolution magic-angle sample spinning (HR-MAS) (1)H NMR spectroscopy of tissue biopsies combined with chemometric techniques has emerged as a valuable methodology for disease diagnosis and environmental assessments. However, the tissue mass required for such experiments is of the order of 10 mg, and this can compromise the metabolic evaluation because of tissue heterogeneity. Tissue availability is often a limitation for clinical studies due to histopathological requirements, which are currently the gold standard for diagnosis, for example, in the case of tumors. Here, we introduce the use of a rotating micro-NMR detector that optimizes the coil filling factor such that mass-limited samples can be measured. We show the results for measuring nanoliter volume tissue biopsies using a commercial HR-MAS probe for the first time. The method has been tested with bovine muscle and human gastric mucosal tumor tissue samples. The gain in mass sensitivity is approximate up to 17-fold, and the adequate spectral resolution (3 Hz) allows the measurement of the metabolite profiles in nanoliter volume samples, thereby limiting the ambiguity resulting from heterogeneous tissues; thus, the approach presents diagnostic potential for studies by metabonomics of mass-limited biopsies.

Identification of human urinary biomarkers of cruciferous vegetable consumption by metabonomic profiling.

Consumption of cruciferous vegetables (CVs) is inversely correlated to many human diseases including cancer (breast, lung, and bladder), diabetes, and cardiovascular and neurological disease. Presently, there are no readily measurable biomarkers of CV consumption and intake of CVs has relied on dietary recall. Here, biomarkers of CV intake were identified in the urine of 20 healthy Caucasian adult males using (1)H NMR spectroscopy with multivariate statistical modeling. The study was separated into three phases of 14 days: a run-in period with restricted CV consumption (phase I); a high CV phase where participants consumed 250 g/day of both broccoli and Brussels sprouts (phase II); a wash-out phase with a return to restricted CV consumption (phase III). Each study participant provided a complete cumulative urine collection over 48 h at the end of each phase; a spot urine (U0), 0-10 h (U0-10), 10-24 h (U10-24), and 24-48 h (U24-48) urine samples. Urine samples obtained after consumption of CVs were differentiated from low CV diet samples by four singlet (1)H NMR spectroscopic peaks, one of which was identified as S-methyl-l-cysteine sulfoxide (SMCSO) and the three other peaks were tentatively identified as other metabolites structurally related to SMCSO. These stable urinary biomarkers of CV consumption will facilitate future assessment of CVs in nutritional population screening and dietary intervention studies and may correlate to population health outcomes.

Pharmacometabonomics as an effector for personalized medicine.

This article introduces and reviews the concept of pharmacometabonomics, with recent experimental exemplifications of the approach being described and discussed. Pharmacometabonomics seeks to predict the response of an individual to a stimulus (e.g., drug, toxin, surgery, nutrition and so on) prior to the stimulus or other perturbation. It is an integral part of top-down systems biology which aims to improve understanding of phenotypic differences and the impact of beneficial and pathological interventions. The pharmacometabonomic concept is also integral to the understanding of mammalian-gut microbiome cometabolic interactions and their consequences, including the impact on disease and therapy. Although the subject is only at an early stage and requires further exemplification and validation, the approach has major implications for improved efficiency in drug discovery efforts, for example, by enabling more careful selection of animals in preclinical studies, for better stratification of patients in drug clinical trials and for individualized therapies. It could also find application in population-wide large cohort studies and in studies of nutrition where it would allow the elucidation of health risk factors and provide easily measured surrogate biomarkers.

Urinary metabolites of 2-bromoethanamine identified by stable isotope labelling: evidence for carbamoylation and glutathione conjugation.

2-Bromoethanamine (BEA) causes renal papillary necrosis (RPN) in rats after a single dose and has been widely used as a model compound for studying the lesion. Although the metabolism of BEA may be an important determinant of toxicity, the metabolic fate of the compound has not been fully elucidated. To date, the only identified BEA metabolites are aziridine, 2-oxazolidone and 5-hydroxy-2-oxazolidone. In this study, stable isotope labelling (SIL) of BEA analogs ((¹³C and ²H) were used to differentiate generated BEA metabolites from endogenous molecules which enabled the accurate liquid chromatography mass spectrometry detection of more than 180 novel metabolites. BEA metabolism was evaluated in rats after acute administration of a non-toxic dose (50 mg/kg) and a toxic dose (250 mg/kg) that caused frank RPN and polyuria. Newly identified metabolites include three carbamoylation products, two mercapturic acids and a group of amino acid conjugates. Overall, the results indicate that BEA metabolism is very complex, suggest the potential formation of reactive intermediates and establish that BEA is subject to conjugation with glutathione. The results also demonstrate the utility and sensitivity of the SIL approach for identification of metabolites from small, reactive compounds.

High-resolution magic-angle-spinning NMR spectroscopy for metabolic profiling of intact tissues.

Metabolic profiling, metabolomic and metabonomic studies require robust study protocols for any large-scale comparisons and evaluations. Detailed methods for solution-state NMR spectroscopy have been summarized in an earlier protocol. This protocol details the analysis of intact tissue samples by means of high-resolution magic-angle-spinning (HR-MAS) NMR spectroscopy and we provide a detailed description of sample collection, preparation and analysis. Described here are (1)H NMR spectroscopic techniques such as the standard one-dimensional, relaxation-edited, diffusion-edited and two-dimensional J-resolved pulse experiments, as well as one-dimensional (31)P NMR spectroscopy. These are used to monitor different groups of metabolites, e.g., sugars, amino acids and osmolytes as well as larger molecules such as lipids, non-invasively. Through the use of NMR-based diffusion coefficient and relaxation times measurements, information on molecular compartmentation and mobility can be gleaned. The NMR methods are often combined with statistical analysis for further metabonomics analysis and biomarker identification. The standard acquisition time per sample is 8-10 min for a simple one-dimensional (1)H NMR spectrum, giving access to metabolite information while retaining tissue integrity and hence allowing direct comparison with histopathology and MRI/MRS findings or the evaluation together with biofluid metabolic-profiling data.

NMR-based metabolic profiling identifies biomarkers of liver regeneration following partial hepatectomy in the rat.

Tissue injury and repair are often overlapping consequences of disease or toxic exposure, but are not often considered as distinct processes in molecular studies. To establish the systemic metabolic response to liver regeneration, the partial hepatectomy (PH) model has been studied in the rat by an integrated metabonomics strategy, utilizing (1)H NMR spectroscopy of urine, liver and serum. Male Sprague-Dawley rats were subjected to either surgical removal of approximately two-thirds of the liver, sham operated (SO) surgery, or no treatment (n = 10/group) and samples collected over a 7 day period. A number of urinary metabolic perturbations were observed in PH rats compared with SO and control animals, including elevated levels of taurine, hypotaurine, creatine, guanidinoacetic acid, betaine, dimethylglycine and bile acids. Serum betaine and creatine were also elevated after PH, while levels of triglyceride were reduced. In the liver, triglycerides, cholesterol, alanine and betaine were elevated after PH, while choline and its derivatives were reduced. Upon examining the dynamic pattern of urinary response (the 'metabolic trajectory'), several metabolites could be categorized into groups likely to reflect perturbations to different processes such as dietary intake or hepatic 1-carbon metabolism. Several of the urinary perturbations observed during the regenerative phase of the PH model have also been observed after exposure to liver toxins, indicating that hepatic regeneration may make a contribution to the systemic alterations in metabolism associated with hepatotoxicity. The observed changes in 1-carbon and lipid metabolism are consistent with the proposed role of these pathways in the activation of a regenerative response and provide further evidence regarding the utility of urinary NMR profiles in the detection of liver-specific pathology. Biofluid (1)H NMR-based metabolic profiling provides new insight into the role of metabolism of liver regeneration, and suggests putative biomarkers for the noninvasive monitoring of the regeneration process.

Heteronuclear 19F-1H statistical total correlation spectroscopy as a tool in drug metabolism: study of flucloxacillin biotransformation.

We present a novel application of the heteronuclear statistical total correlation spectroscopy (HET-STOCSY) approach utilizing statistical correlation between one-dimensional 19F/1H NMR spectroscopic data sets collected in parallel to study drug metabolism. Parallel one-dimensional (1D) 800 MHz 1H and 753 MHz 19F{1H} spectra (n = 21) were obtained on urine samples collected from volunteers (n = 6) at various intervals up to 24 h after oral dosing with 500 mg of flucloxacillin. A variety of statistical relationships between and within the spectroscopic datasets were explored without significant loss of the typically high 1D spectral resolution, generating 1H-1H STOCSY plots, and novel 19F-1H HET-STOCSY, 19F-19F STOCSY, and 19F-edited 1H-1H STOCSY (X-STOCSY) spectroscopic maps, with a resolution of approximately 0.8 Hz/pt for both nuclei. The efficient statistical editing provided by these methods readily allowed the collection of drug metabolic data and assisted structure elucidation. This approach is of general applicability for studying the metabolism of other fluorine-containing drugs, including important anticancer agents such as 5-fluorouracil and flutamide, and is extendable to any drug metabolism study where there is a spin-active X-nucleus (e.g., 13C, 15N, 31P) label present.

Magic angle spinning NMR and 1H-31P heteronuclear statistical total correlation spectroscopy of intact human gut biopsies.

Previously we have demonstrated the use of 1H magic angle spinning (MAS) NMR spectroscopy for the topographical variations in functional metabolic signatures of intact human intestinal biopsy samples. Here we have analyzed a series of MAS 1H NMR spectra (spin-echo, one-dimensional, and diffusion-edited) and 31P-{1H} spectra and focused on analyzing the enhancement of information recovery by use of the statistical total correlation spectroscopy (STOCSY) method. We have applied a heterospectroscopic cross-examination performed on the same samples and between 1H and 31P-{1H} spectra (heteronuclear STOCSY) to recover latent metabolic information. We show that heterospectroscopic correlation can give new information on the molecular compartmentation of metabolites in intact tissues, including the statistical "isolation" of a phospholipid/triglyceride vesicle pool in intact tissue. The application of 31P-1H HET-STOCSY allowed the cross-assignment of major 31P signals to their equivalent 1H NMR spectra, e.g., for phosphorylcholine and phosphorylethanolamine. We also show pathway correlations, e.g., the ascorbate-glutathione pathway, in the STOCSY analysis of intact tissue spectra. These 31P-1H HET-STOCSY spectra also showed different topographical regions, particular for minor signals in different tissue microenvironments. This approach could be extended to allow the detection of altered distributions within metabolic subcompartments as well as conventional metabonomics concentration-based diagnostics.

Topographical variation in metabolic signatures of human gastrointestinal biopsies revealed by high-resolution magic-angle spinning 1H NMR spectroscopy.

Individual and topographical variation in the metabolic profiles of multiple human gastrointestinal tract (GIT) biopsies have been characterized using high-resolution magic-angle spinning (HRMAS) 1H NMR spectroscopy and pattern recognition. Samples from antrum, duodenum, jejunum, ileum, and transverse colon were obtained from 8 male and 8 female participants. Each gut region generated a highly characteristic metabolic profile consistent with the varying structural and functional properties of the tissue at different longitudinal levels of the gut. The antral (stomach) mucosa contained higher levels of choline, glycogen, phosphorylethanolamine, and taurine than other gut regions. The spatially close regions of the duodenum and jejunum were equivalent in terms of their gross biochemical composition with high levels of choline, glutathione, glycerophosphocholine (GPC), and lipids relative to other gut regions. The ileal mucosa showed poor discrimination from the duodenum and jejunum tissues and generated strong amino acids signatures but had relative low GPC signals. The colon (large intestine) was high in acetate, glutamate, inositols, and lactate and low in creatine, GPC, and taurine compared to the small intestine. These longitudinal metabolic variations in the human GIT could be attributed to functional variations in energy metabolism, osmoregulation, gut microbial activity, and oxidative protection. This work indicates that 1H HRMAS NMR studies may be of value in analyzing local metabolic variation due to pathological processes in gut biopsies.

A high-performance liquid chromatography and nuclear magnetic resonance spectroscopy-based analysis of commercially available praziquantel tablets.

The amount of active ingredient in 20 commercially sourced batches of praziquantel (PZQ) tablets was determined using a high-performance liquid chromatography-ultraviolet (HPLC-UV) assay in conjunction with an anthentic, lot of PZQ powder. The general composition of each batch of tablets was also examined by means of (1)H nuclear magnetic resonance (NMR) spectroscopy and the NMR data were subjected to pattern recognition analysis by means of principal component analysis. The HPLC-UV results showed that each batch of PZQ tablets contained approximately the required amount of PZQ (600 mg per tablet). The NMR analysis showed a high degree of compositional variation between manufacturers, which caused by variation in excipients, along with some batch-to-batch variation in the tablets from a single manufacturer. Additionally, the PZQ tablets from one manufacturer were found to have an extra component (methyl-4-hydroxybenzoate) that was not detected in the other preparations.

Metabolic assessment of human liver transplants from biopsy samples at the donor and recipient stages using high-resolution magic angle spinning 1H NMR spectroscopy.

This work presents the first application of high-resolution magic angle spinning (HR-MAS) 1H NMR spectroscopy to human liver biopsy samples, allowing a determination of their metabolic profiles before removal from donors, during cold perfusion, and after implantation into recipients. The assignment of peaks observed in the 1H HR-MAS NMR spectra was aided by the use of two-dimensional J-resolved, TOCSY and 1H-13C HMQC spectra. The spectra were dominated by resonances from triglycerides, phospholipids, and glycogen and from a variety of small molecules including glycerophosphocholine (GPC), glucose, lactate, creatine, acetate, amino acids, and nucleoside-related compounds such as uridine and adenosine. In agreement with histological data obtained on the same biopsies, two of the six livers were found to contain high amounts of triglycerides by NMR spectroscopy, which also indicated that these tissues contained a higher degree of unsaturated lipids and a lower proportion of phospholipids and low molecular weight compounds. Additionally, proton T2 relaxation times indicated two populations of lipids, a higher mobility triglyceride fraction and a lower mobility phospholipid fraction, the proportions of which changed according to the degree of fat content. GPC was found to decrease from the pretransplant to the posttransplant biopsy of all livers except for one with a histologically confirmed high lipid content, and this might represent a biomarker of liver function posttransplantation. NMR signals produced by the liver preservation solution were clearly detected in the cold perfusion stage biopsies of all livers but remained in the posttransplant spectra of only the two livers with a high lipid content and were prominent mainly in the graft that later developed primary graft dysfunction. This study has shown biochemical differences between livers used for transplants that can be related to the degree and type of lipid composition. This technology might therefore provide a novel screening approach for donor organ quality and a means to assess function in the recipient after transplantation.

Automatic alignment of individual peaks in large high-resolution spectral data sets.

Pattern recognition techniques are effective tools for reducing the information contained in large spectral data sets to a much smaller number of significant features which can then be used to make interpretations about the chemical or biochemical system under study. Often the effectiveness of such approaches is impeded by experimental and instrument induced variations in the position, phase, and line width of the spectral peaks. Although characterizing the cause and magnitude of these fluctuations could be important in its own right (pH-induced NMR chemical shift changes, for example) in general they obscure the process of pattern discovery. One major area of application is the use of large databases of (1)H NMR spectra of biofluids such as urine for investigating perturbations in metabolic profiles caused by drugs or disease, a process now termed metabonomics. Frequency shifts of individual peaks are the dominant source of such unwanted variations in this type of data. In this paper, an automatic procedure for aligning the individual peaks in the data set is described and evaluated. The proposed method will be vital for the efficient and automatic analysis of large metabonomic data sets and should also be applicable to other types of data.

Integrated application of transcriptomics and metabonomics yields new insight into the toxicity due to paracetamol in the mouse.

Gene chip array (Affymetrix) data from liver tissue and high resolution 1H NMR spectra from intact liver tissue, tissue extracts and plasma have been analyzed to identify biochemical changes arising from hepatotoxicity in mice dosed with acetaminophen. These data sets have been co-interpreted in terms of common metabolic pathways. The principal metabolic changes comprised a decrease in hepatic glucose and glycogen in intact tissue, coupled with an increase in lipid content, with increases in the levels of glucose, pyruvate, acetate and lactate in plasma, and increases in alanine and lactate in the aqueous tissue extracts. Collectively these data provide evidence for an increased rate of hepatic glycolysis. The metabolic observations were consistent with the altered levels of gene expression relating to lipid and energy metabolism in liver which both preceded and were concurrent with the metabolic perturbations. The results show that these two technology platforms together offer a complementary view into cellular responses to toxic processes, providing new insight into the toxic consequences, even for well-studied therapeutic agents such as acetaminophen.