NMR-based metabonomic approaches for evaluating physiological influences on biofluid composition

Analysis of the metabolic profile of humans naturally exposed to RF-EM radiation

INTRODUCTION

The world is experiencing exponential growth in communication, especially wireless communication. Wireless connectivity has recently become a part of everyone's daily life. Recent developments in low-cost, low-power, and miniature devices contribute to a significant rise in radiofrequency-electromagnetic field (RF-EM) radiation exposure in our environment, raising concern over its effect on biological systems. The inconsistent and conflicting research results make it difficult to draw definite conclusions about how RF-EM radiation affects living things.

OBJECTIVES

This study identified two micro-environments based on their level of exposure to cellular RF-EM radiation, one with significantly less exposure and another with very high exposure to RF-EM radiation. Emphasis is given to studying the metabolites in the urine samples of humans naturally exposed to these two different microenvironments to understand short-term metabolic dysregulations.

METHODS

Untargeted 1H NMR spectroscopy was employed for metabolomics analyses to identify dysregulated metabolites. A total of 60 subjects were recruited with 5 ml urine samples each. These subjects were divided into two groups: one highly exposed to RF-EM (n = 30) and the other consisting of low-exposure populations (n = 30).

RESULTS

The study found that the twenty-nine metabolites were dysregulated. Among them, 19 were downregulated, and 10 were upregulated. In particular, Glyoxylate and dicarboxylate and the TCA cycle metabolism pathway have been perturbed. The dysregulated metabolites were validated using the ROC curve analysis.

CONCLUSION

Untargeted urine metabolomics was conducted to identify dysregulated metabolites linked to RF-EM radiation exposure. Preliminary findings suggest a connection between oxidative stress and gut microbiota imbalance. However, further research is needed to validate these biomarkers and understand the effects of RF-EM radiation on human health. Further research is needed with a diverse population.

Exploring the Potential Role of Metabolomics in COPD: A Concise Review

Chronic Obstructive Pulmonary Disease (COPD) is a pathological condition of the respiratory system characterized by chronic airflow obstruction, associated with changes in the lung parenchyma (pulmonary emphysema), bronchi (chronic bronchitis) and bronchioles (small airways disease). In the last years, the importance of phenotyping and endotyping COPD patients has strongly emerged. Metabolomics refers to the study of metabolites (both intermediate or final products) and their biological processes in biomatrices. The application of metabolomics to respiratory diseases and, particularly, to COPD started more than one decade ago and since then the number of scientific publications on the topic has constantly grown. In respiratory diseases, metabolomic studies have focused on the detection of metabolites derived from biomatrices such as exhaled breath condensate, bronchoalveolar lavage, and also plasma, serum and urine. Mass Spectrometry and Nuclear Magnetic Resonance Spectroscopy are powerful tools in the precise identification of potentially prognostic and treatment response biomarkers. The aim of this article was to comprehensively review the relevant literature regarding the applications of metabolomics in COPD, clarifying the potential clinical utility of the metabolomic profile from several biologic matrices in detecting biomarkers of disease and prognosis for COPD. Meanwhile, a complete description of the technological instruments and techniques currently adopted in the metabolomics research will be described.

Application of response surface methodology and quantitative NMR for the optimum extraction, characterization, and quantitation of Antrodia cinnamomea triterpenoids

Antrodia cinnamomea (AC) is a treasured Asian medicinal mushroom, which has attracted attention due to recent research on its effectiveness in targeting a variety of serious ailments such as cancer and liver diseases. Among different A. cinnamomea constituents, triterpenoids are regarded as the most therapeutically attractive components because of their anti-inflammatory and cytotoxic activities. In the present study, we proposed a mathematical and statistical extraction protocol to evaluate the concentrations of total ergostane and lanostane triterpenoid derivatives from the ethanolic extract of the wild fruiting bodies of A. cinnamomea (EEAC) by utilizing response surface methodology (RSM) and quantitative NMR (qNMR) approaches. The optimum response surface model showed that the variations of the investigated response variables reached more than 90%, suggesting that the developed model is accurate in explaining response variability. Furthermore, the EEAC major characteristic triterpenoids were quantified through the comparison of the HPLC-tandem MS results with those of the qNMR results. The precision of the used techniques was also evaluated. The experimental design of the EEAC optimum extraction procedure obtained by using RSM and qNMR enabled accurate characterization and quantitation of A. cinnamomea triterpenoids.

Pipecolate and Taurine are Rat Urinary Biomarkers for Lysine and Threonine Deficiencies

BACKGROUND

The consumption of poor-quality protein increases the risk of essential amino acid (EAA) deficiency, particularly for lysine and threonine. Thus, it is necessary to be able to detect easily EAA deficiency.

OBJECTIVES

The purpose of this study was to develop metabolomic approaches to identify specific biomarkers for an EAA deficiency, such as lysine and threonine.

METHODS

Three experiments were performed on growing rats. In experiment 1, rats were fed for 3 weeks with lysine (L30), or threonine (T53)-deficient gluten diets, or nondeficient gluten diet (LT100) in comparison with the control diet (milk protein, PLT). In experiments 2a and 2b, rats were fed at different concentrations of lysine (L) or threonine (T) deficiency: L/T15, L/T25, L/T40, L/T60, L/T75, P20, L/T100 and L/T170. Twenty-four-hour urine and blood samples from portal vein and vena cava were analyzed using LC-MS. Data from experiment 1 were analyzed by untargeted metabolomic and Independent Component - Discriminant Analysis (ICDA) and data from experiments 2a and 2b by targeted metabolomic and a quantitative Partial Least- Squares (PLS) regression model. Each metabolite identified as significant by PLS or ICDA was then tested by 1-way ANOVA to evaluate the diet effect. A two-phase linear regression analysis was used to determine lysine and threonine requirements.

RESULTS

ICDA and PLS found molecules that discriminated between the different diets. A common metabolite, the pipecolate, was identified in experiments 1 and 2a, confirming that it could be specific to lysine deficiency. Another metabolite, taurine, was found in experiments 1 and 2b, so probably specific to threonine deficiency. Pipecolate or taurine breakpoints obtained give a value closed to the values obtained by growth indicators.

CONCLUSIONS

Our results showed that the EAA deficiencies influenced the metabolome. Specific urinary biomarkers identified could be easily applied to detect EAA deficiency and to determine which AA is deficient.

Assessing the Acute Toxicological Effects of Annona muricata Leaf Ethanol Extract on Rats: Biochemical, Histopathological, and Metabolomics Analyses

Annona muricata is a common plant used in Africa and South America to manage various types of disease. However, there is insufficient toxicological information or published standard available regarding repeated dose animal toxicity data. As part of the safety assessment, we exposed Sprague Dawley rats to an acute oral toxicity of A. muricata. The intent of the current study was to use advanced proton nuclear magnetic resonance (1H NMR) in serum and urinary metabolomics evaluation techniques to provide the in vivo acute toxicological profile of A. muricata leaf ethanol extract in accordance with the Organization for Economic Co-operation and Development's (OECD) 423 guidelines. A single 2000 mg/kg dose of A. muricata leaf ethanol extract was administered to Sprague Dawley rats over an observational period of 14 days. The toxicity evaluation (physical and behavior observation, body weight, renal function test, liver function test and 1H NMR analysis) showed no abnormal toxicity. Histopathological analysis manifested mild changes, i.e., the treated kidney manifested mild hypercellularity of mesangial cells and mild red blood cell congestion. In addition, there was mild hemorrhage into tissue with scattered inflammatory cells and mild dilated central vein with fibrosis in the liver. However, the changes were very mild and not significant which correlate with other analyses conducted in this study (biochemical test and 1H NMR metabolomic analysis). On the other hand, urinary 1H NMR analysis collected on day 15 revealed high similarity on the metabolite variations for both untreated and treated groups. Importantly, the outcomes suggest that A. muricata leaf ethanol extract can be safely consumed at a dose of 2000 mg/kg and the LD50 must be more than 2000 mg/kg.

Linking research of biomedical datasets

Biomedical data preprocessing and efficient computing can be as important as the statistical methods used to fit the data; data processing needs to consider application scenarios, data acquisition and individual rights and interests. We review common principles, knowledge and methods of integrated research according to the whole-pipeline processing mechanism diverse, coherent, sharing, auditable and ecological. First, neuromorphic and native algorithms integrate diverse datasets, providing linear scalability and high visualization. Second, the choice mechanism of different preprocessing, analysis and transaction methods from raw to neuromorphic was summarized on the node and coordinator platforms. Third, combination of node, network, cloud, edge, swarm and graph builds an ecosystem of cohort integrated research and clinical diagnosis and treatment. Looking forward, it is vital to simultaneously combine deep computing, mass data storage and massively parallel communication.

1H NMR Urinary Metabolomic Analysis in Older Adults after Hip Fracture Surgery May Provide Valuable Information for Patient Profiling-A Preliminary Investigation

In these times of precision and personalized medicine, profiling patients to identify their needs is crucial to providing the best and most cost-effective treatment. In this study, we used urine metabolomics to explore the characterization of older adults with hip fractures and to explore the forecasting of patient outcomes. Overnight urine specimens were collected from 33 patients (mean age 80 ± 8 years) after hip fracture surgery during their stay at a rehabilitation hospital. The specimens were analyzed with ¹H NMR spectroscopy. We performed a metabolomics study regarding assessments of frailty status, Functional Independence Measure (FIM), and Short Physical Performance Battery (SPPB). The main metabolic variations concerned 10 identified metabolites: paracetamol derivatives (4 peaks: 2.15 ppm; 2.16 ppm; 7.13 ppm and 7.15 ppm); hippuric acid; acetate; acetone; dimethylamine; glycine; alanine; lactate; valine; TMAO. At baseline, the urinary levels of these metabolites were significantly higher (i) in frail compared with non-frail patients, (ii) in persons with poorer FIM scores, and (iii) in persons with poorer compared SPPB scores. Our findings suggested that patients with increased levels of urine metabolites associated with metabolic, inflammatory, and renal disorders presented clear signs of frailty, impaired functional independence, and poor physical performance. Metabolomics could be a valuable tool to further characterize older adults, especially after major medical events.

Balancing the Equation: A Natural History of Trimethylamine and Trimethylamine-N-oxide

Trimethylamine (TMA) and its N-oxide (TMAO) are ubiquitous in prokaryote and eukaryote organisms as well as in the environment, reflecting their fundamental importance in evolutionary biology, and their diverse biochemical functions. Both metabolites have multiple biological roles including cell-signaling. Much attention has focused on the significance of serum and urinary TMAO in cardiovascular disease risk, yet this is only one of the many facets of a deeper TMA-TMAO partnership that reflects the significance of these metabolites in multiple biological processes spanning animals, plants, bacteria, and fungi. We report on analytical methods for measuring TMA and TMAO and attempt to critically synthesize and map the global functions of TMA and TMAO in a systems biology framework.

Metabolomic Studies in Inner Ear Pathologies

Sensorineural hearing loss is the most common sensory deficit. The etiologies of sensorineural hearing loss have been described and can be congenital or acquired. For congenital non-syndromic hearing loss, mutations that are related to sites of cochlear damage have been discovered (e.g., connexin proteins, mitochondrial genes, etc.). For cytomegalovirus infection or auditory neuropathies, mechanisms are also well known and well researched. Although the etiologies of sensorineural hearing loss may be evident for some patients, the damaged sites and pathological mechanisms remain unclear for patients with progressive post-lingual hearing loss. Metabolomics is an emerging technique in which all metabolites present in a sample at a given time are analyzed, reflecting a physiological state. The objective of this study was to review the literature on the use of metabolomics in hearing loss. The findings of this review suggest that metabolomic studies may help to develop objective tests for diagnosis and personalized treatment.

Identification of biomarkers in COPD by metabolomics of exhaled breath condensate and serum/plasma

Chronic obstructive pulmonary disease (COPD) is the third cause of death worldwide, presenting poor long-term outcomes and chronic disability. COPD is a condition with a wide spectrum of clinical presentations because its pathophysiological determinants relate to tobacco smoke, genetic factors, alteration of several metabolic pathways, and oxidative stress. As a consequence, patients present different phenotypes even with comparable degrees of airflow limitation. Because of the increasing social and economic costs of COPD, a growing attention is currently payed to "omics" techniques for more personalized treatments and patient-tailored rehabilitation programs. In this regard, the systematic investigation of the metabolome (i.e., the whole set of endogenous molecules) in biomatrices, namely metabolomics, has become indispensable for phenotyping respiratory diseases. The metabolomic profiling of biological samples contains the small molecules produced during biological processes and their identification and quantification help in the diagnosis, comprehension of disease outcome and treatment response. Exhaled breath condensate (EBC), plasma and serum are biofluids readily available, with negligible invasiveness, and, therefore, suitable for metabolomics investigations. In this paper, we describe the latest advances on metabolomic profiling of EBC, plasma and serum in COPD patients.

Use of Tannin-Containing Plants as Antimicrobials Influencing the Animal Health

The antimicrobial effects of diverse tannin-containing plants, particularly condensed tannins (CTs) produced from various plants, are the subject of this study. CT components can be determined using CT-specific procedures such the HCl-Butanol Acetone assay, Thiolysis reaction, and HPLC/MS analysis. These methods indicate CT contents, including mean degree of polymerization, the procyanidins and prodelphinidins ratio (PC/PD%), the isomers of trans- and cis-, and CT concentration. Tannin-containing plants possess antibacterial action, which can be attributed to their protein linkage technique, and tannin-type variations, particularly CTs extract and their PC/PD%. The effects of CT components on the development of Gram-positive and Gram-negative bacteria have been documented for their relative PC/PD%; this is regarded to be a key predictor of tannin characteristics in terms of antimicrobials. In conclusion, tannins, more specific CT compositions, have significant impacts on in vivo trials of animal productions and utilization of metabolites and fermentation in vitro experiments. These findings need further investigations to fully understand how CT-types act on animal feeding in terms of enhanced nutritional quality of animal diets, which may have implications for human and animal health.

Metabolomic profiling of exhaled breath condensate and plasma/serum in chronic obstructive pulmonary disease

Chronic obstructive pulmonary disease (COPD) is an increasing cause of global morbidity and mortality, with poor long-term outcomes and chronic disability. COPD is a condition with a wide spectrum of clinical presentations, with different phenotypes being identified even among patients with comparable degrees of airflow limitation. Considering the burden of COPD in terms of social and economic costs, in recent years a growing attention has been given to the need of more personalized approaches and patient-tailored rehabilitation programs. In this regard, the systematic analysis of metabolites in biological matrices, namely metabolomics, may become an essential tool in phenotyping diseases. Through the identification and quantification of the small molecules produced during biological processes, metabolomic profiling of biological samples has thus been proposed as an opportunity to identify novel biomarkers of disease outcome and treatment response. Exhaled breath condensate (EBC) and plasma/serum are fluid pools, which can be easily extracted and analyzed. In this review, we discuss the potential clinical applications of the metabolomic profiling of EBC and plasma/serum in COPD.

Plasma and Urinary Amino Acid-Derived Catabolites as Potential Biomarkers of Protein and Amino Acid Deficiency in Rats

OBJECTIVE

Dietary intakes must cover protein and essential amino acid (EAA) requirements. For this purpose, different methods have been developed such as the nitrogen balance method, factorial method, or AA tracer studies. However, these methods are either invasive or imprecise, and the Food and Agriculture Organization of the United Nations (FAO, 2013) recommends new methods and, in particular, metabolomics. The aim of this study is to determine total protein/EAA requirement in the plasma and urine of growing rats.

METHODS

36 weanling rats were fed with diets containing 3, 5, 8, 12, 15, and 20% protein for 3 weeks. During experimentation, urine was collected using metabolic cages, and blood from the portal vein and vena was taken at the end of the experiment. Metabolomics analyses were performed using LC-MS, and the data were analyzed with a multivariate analysis model, partial least Squares (PLS) regression, and independent component-discriminant analysis (ICDA). Each discriminant metabolite identified by PLS or ICDA was tested by one-way ANOVA to evaluate the effect of diet.

RESULTS

PLS and ICDA allowed us to identify discriminating metabolites between different diet groups. Protein deficiency led to an increase in the AA catabolism enzyme systems inducing the production of breakdown metabolites in the plasma and urine.

CONCLUSION

These results indicate that metabolites are specific for the state of EAA deficiency and sufficiency. Some types of biomarkers such as AA degradation metabolites appear to be specific candidates for protein/EAA requirement.

NMR-Based Metabolomic Analysis for the Effects of α-Ketoglutarate Supplementation on C2C12 Myoblasts in Different Energy States

α-Ketoglutarate (AKG) is attracting much attention from researchers owing to its beneficial effects on anti-aging and cancer suppression, and, more recently, in nutritional supplements. Given that glucose is the main source of energy to maintain normal physiological functions of skeletal muscle, the effects of AKG supplementation for improving muscle performance are closely related to the glucose level in skeletal muscle. The differences of AKG-induced effects in skeletal muscle between two states of normal energy and energy deficiency are unclear. Furthermore, AKG-induced metabolic changes in skeletal muscles in different energy states also remain elusive. Here, we assessed the effects of AKG supplementation on mouse C2C12 myoblast cells cultured both in normal medium (Nor cells) and in low-glucose medium (Low cells), which were used to mimic two states of normal energy and energy deficiency, respectively. We further performed NMR-based metabolomic analysis to address AKG-induced metabolic changes in Nor and Low cells. AKG supplementation significantly promoted the proliferation and differentiation of cells in the two energy states through glutamine metabolism, oxidative stress, and energy metabolism. Under normal culture conditions, AKG up-regulated the intracellular glutamine level, changed the cellular energy status, and maintained the antioxidant capacity of cells. Under low-glucose culture condition, AKG served as a metabolic substrate to reduce the glutamine-dependence of cells, remarkably enhanced the antioxidant capacity of cells and significantly elevated the intracellular ATP level, thereby ensuring the normal growth and metabolism of cells in the state of energy deficiency. Our results provide a mechanistic understanding of the effects of AKG supplements on myoblasts in both normal energy and energy deficiency states. This work may be beneficial to the exploitation of AKG applications in clinical treatments and nutritional supplementations.

Analytical Tools for Disease Diagnosis in Animals via Fecal Volatilome

Volatilome analysis is growing in attention for the diagnosis of diseases in animals and humans. In particular, volatilome analysis in fecal samples is starting to be proposed as a fast, easy and noninvasive method for disease diagnosis. Volatilome comprises volatile organic compounds (VOCs), which are produced during both physiological and patho-physiological processes. Thus, VOCs from a pathological condition often differ from those of a healthy state and therefore the VOCs profile can be used in the detection of some diseases. Due to their strengths and advantages, feces are currently being used to obtain information related to health status in animals. However, they are complex samples, that can present problems for some analytical techniques and require special consideration in their use and preparation before analysis. This situation demands an effort to clarify which analytic options are currently being used in the research context to analyze the possibilities these offer, with the final objectives of contributing to develop a standardized methodology and to exploit feces potential as a diagnostic matrix. The current work reviews the studies focused on the diagnosis of animal diseases through fecal volatilome in order to evaluate the analytical methods used and their advantages and limitations. The alternatives found in the literature for sampling, storage, sample pretreatment, measurement and data treatment have been summarized, considering all the steps involved in the analytical process.

Robust Metabolite Quantification from J-Compensated 2D 1H-13C-HSQC Experiments

The spectral resolution of 2D 1H-13C heteronuclear single quantum coherence (1H-13C-HSQC) nuclear magnetic resonance (NMR) spectra facilitates both metabolite identification and quantification in nuclear magnetic resonance-based metabolomics. However, quantification is complicated by variations in magnetization transfer, which among others originate mainly from scalar coupling differences. Methods that compensate for variation in scalar coupling include the generation of calibration factors for individual signals or the use of additional pulse sequence schemes such as quantitative HSQC (Q-HSQC) that suppress the J_CH-dependence by modulating the polarization transfer delays of HSQC or, additionally, employ a pure-shift homodecoupling approach in the 1H dimension, such as Quantitative, Perfected and Pure Shifted HSQC (QUIPU-HSQC). To test the quantitative accuracy of these three methods, employing a 600 MHz NMR spectrometer equipped with a helium cooled cryoprobe, a Latin-square design that covered the physiological concentration ranges of 10 metabolites was used. The results show the suitability of all three methods for the quantification of highly abundant metabolites. However, the substantially increased residual water signal observed in QUIPU-HSQC spectra impeded the quantification of low abundant metabolites located near the residual water signal, thus limiting its utility in high-throughput metabolite fingerprinting studies.

Urinary metabolomic investigations in vitiligo patients

Urinary metabolomics is a useful non-invasive tool for large-scale screening of disease-related metabolites. However, no comprehensive urinary metabolomic analysis of vitiligo is presently available. To investigate the urine metabolic pattern of vitiligo patients, we conducted a combined cross-sectional and prospective self-control cohort study and an untargeted urinary metabolomic analysis. In the cross-sectional study, 295 vitiligo patients and 192 age‐ and sex‐matched controls were enrolled, and 71 differential metabolites between two groups were identified. Pathway enrichment analysis revealed that drug metabolism-cytochrome P450, biopterin metabolism, vitamin B9 (folate) metabolism, selenoamino acid metabolism, and methionine and cysteine metabolism showed significant enrichment in vitiligo patients compared with the status in healthy controls. In the self-control cohort, 46 active vitiligo patients were recruited to analyse the urinary metabolic signatures after treatment. All of these patients were asked to undertake follow-up visits every 2 months three times after first consulting and the disease stage was evaluated compared with that at the last visit. Folate metabolism, linoleate metabolism, leukotriene metabolism, alkaloid biosynthesis, and tyrosine metabolism were predicted to be involved in vitiligo activity. Our study is the first attempt to reveal urinary metabolic signatures of vitiligo patients and provides new insights into the metabolic mechanisms of vitiligo.

Machine learning assistive rapid, label-free molecular phenotyping of blood with two-dimensional NMR correlational spectroscopy

Translation of the findings in basic science and clinical research into routine practice is hampered by large variations in human phenotype. Developments in genotyping and phenotyping, such as proteomics and lipidomics, are beginning to address these limitations. In this work, we developed a new methodology for rapid, label-free molecular phenotyping of biological fluids (e.g., blood) by exploiting the recent advances in fast and highly efficient multidimensional inverse Laplace decomposition technique. We demonstrated that using two-dimensional T1-T2 correlational spectroscopy on a single drop of blood (<5 μL), a highly time- and patient-specific 'molecular fingerprint' can be obtained in minutes. Machine learning techniques were introduced to transform the NMR correlational map into user-friendly information for point-of-care disease diagnostic and monitoring. The clinical utilities of this technique were demonstrated through the direct analysis of human whole blood in various physiological (e.g., oxygenated/deoxygenated states) and pathological (e.g., blood oxidation, hemoglobinopathies) conditions.

Comprehensive Targeted Metabolomic Assay for Urine Analysis

Among all the human biological fluids used for disease biomarker discovery or clinical chemistry, urine stands out. It can be collected easily and noninvasively, it is readily available in large volumes, it is typically free from protein contamination, and it is chemically complex-reflecting a wide range of physiological states and functions. However, the comprehensive metabolomic analysis of urine has been somewhat less studied compared to blood. Indeed, most published metabolomic assays are specifically optimized for serum or plasma. In an effort to improve this situation, we have developed a comprehensive, quantitative MS-based assay for urine analysis. The assay robustly detects and quantifies 142 urinary metabolites including 28 amino acids and derivatives, 17 organic acids, 22 biogenic amines and derivatives, 40 acylcarnitines, 34 lipids, and glucose/hexose, among which 67 metabolites are absolutely quantified and 75 metabolites are semiquantified. All the analysis methods in this assay are based on liquid chromatography-tandem mass spectrometry (LC-MS/MS) using both positive and negative-mode multiple reaction monitoring (MRM). The recovery rates of spiked urine samples at three different concentration levels, that is, low, medium and high, are in the range of 80% to 120% with satisfactory precision values of less than 20%. This targeted metabolomic assay has been successfully applied to the analysis of large numbers of human urine samples, with results closely matching those reported in the literature as well as those obtained from orthogonal analysis via NMR spectroscopy. Moreover, the assay was specifically developed in a 96-well plate format, which enables automated, high-throughput sample analysis. The assay has already been used to analyze more than 1800 urine samples in our laboratory since early 2019.

A longitudinal serum NMR-based metabolomics dataset of ischemia-reperfusion injury in adult cardiac surgery

Cardiovascular disease is the leading cause of death worldwide and cardiac surgery is a key treatment. This study explores metabolite changes as a consequence of ischemia-reperfusion due to cardiac surgery with the use of cardiopulmonary bypass (CPB). To describe the ischemia-reperfusion injury, metabolite changes were monitored in fifty patients before and after CPB at multiple time points. We describe a longitudinal metabolite dataset containing nearly 600 serum nuclear magnetic resonance (NMR) spectra obtained from samples collected simultaneously from the pulmonary artery (deoxygenated blood) and left atrium (oxygenated blood) before ischemia (pre-CPB), immediately after reperfusion (end-CPB), and the following 2, 4, 8, and 20 hours postoperatively. In addition, a longitudinal dataset including 57 quantified metabolites is also provided. These datasets will help researchers studying ischemia-reperfusion injury, as well as the time-dependent alterations related to the surgical trauma and the subsequent processes required in regaining metabolite balance. The datasets could also be used for the development of processing algorithms for NMR-based metabolomics studies and methods for the analysis of longitudinal multivariate data.

Measurement(s)	human blood serum metabolite
Technology Type(s)	one-dimensional nuclear magnetic resonance spectroscopy
Factor Type(s)	cardiac surgery • time series • pulmonary artery and left atrium
Sample Characteristic - Organism	Homo sapiens

Machine-accessible metadata file describing the reported data: 10.6084/m9.figshare.12249065

Human urine 1H NMR metabolomics reveals alterations of protein and carbohydrate metabolism when comparing habitual Average Danish diet vs. healthy New Nordic diet

OBJECTIVES

The aim of this study was to investigate the alteration of the human urine metabolome by means of diet and to compare the metabolic effects of the nutritionally healthy New Nordic Diet (NND) with an Average Danish Diet (ADD). The NND was designed a decade ago by scientists and chefs, based on local and sustainable foods, including fish, shellfish, vegetables, roots, fruit, and berries. The NND has been proven to lower blood pressure, reduce glycemia, and lead to weight loss.

METHODS

The human urine metabolome was measured by untargeted proton nuclear magnetic resonance spectroscopy in samples from 142 centrally obese Danes (20-66 years old), randomized to consume the ADD or the NND. The resulting metabolomics data was processed and analyzed using advanced multivariate data analysis methods to reveal effects related to the design factors, including diet, season, sex, and changes in body weight.

RESULTS

Exploration of the nuclear magnetic resonance profiles revealed unique metabolite markers reflecting changes in protein and carbohydrate metabolism between the two diets. Glycine betaine, glucose, trimethylamine N-oxide and creatinine were increased in urine of the individuals following the NND compared with the ADD population, whereas relative concentrations of tartrate, dimethyl sulfone, and propylene glycol were decreased. Propylene glycol had a strong association with the homeostatic model assessment for insulin resistance in the NND group. The food intake biomarkers found in this study confirm the importance of these as tools for nutritional research.

CONCLUSIONS

Findings from this study provided new insights into the effects of a healthy diet on glycemia, reduction of inflammation, and weight loss among obese individuals, and alteration of the gut microbiota metabolism.

Twenty years of metabonomics: so what has metabonomics done for toxicology?

In 1999 the journal Xenobiotica published a perspective article detailing the new concept of metabonomics and its application to toxicology. The approach was to apply analytical chemistry techniques, and in particular ¹H NMR spectroscopy, to profile biofluids and tissues to assess the metabolic effects of xenobiotics. Metabonomics has been shown to be sensitive not only to organ specific toxicity but also provides information on the cells, tissues and mechanisms involved, as well as their interactions with the host's sex, age, diet and environment. This review assesses the impact of metabonomics on drug toxicology over the past twenty years and its future prospects. These applications include:Pharmacometabonomics - the prediction of drug effects through the analysis of predose, biofluid metabolite profiles, which reflect both genetic and environmental influences on physiology.The microbiomes role in toxicology - understanding how xenobiotics can be modified by the microbiome dramatically changing their impact on the host.Development of expert systems for toxicity prediction.Data fusion of different omics to better understand the underlying mechanisms of drug toxicity.Metabonomics and exposome - understanding how multiple environmental toxicants might interact with the host organism to produce their overall phenotype. While there has been huge growth in the use of metabonomics within toxicology these applications are set to increase as the tools become more sensitive and robust, as well as the increased use of both experimental and in silico databases to aid prediction of toxicology.

Metabolomics and Heart Diseases: From Basic to Clinical Approach

BACKGROUND

The field of metabolomics has been steadily increasing in size for the last 15 years. Advances in analytical and statistical methods have allowed metabolomics to flourish in various areas of medicine. Cardiovascular diseases are some of the main research targets in metabolomics, due to their social and medical relevance, and also to the important role metabolic alterations play in their pathogenesis and evolution. Metabolomics has been applied to the full spectrum of cardiovascular diseases: from patient risk stratification to myocardial infarction and heart failure. However - despite the many proof-ofconcept studies describing the applicability of metabolomics in the diagnosis, prognosis and treatment evaluation in cardiovascular diseases - it is not yet used in routine clinical practice. Recently, large phenome centers have been established in clinical environments, and it is expected that they will provide definitive proof of the applicability of metabolomics in clinical practice. But there is also room for small and medium size centers to work on uncommon pathologies or to resolve specific but relevant clinical questions.

OBJECTIVES

In this review, we will introduce metabolomics, cover the metabolomic work done so far in the area of cardiovascular diseases.

CONCLUSION

The cardiovascular field has been at the forefront of metabolomics application and it should lead the transfer to the clinic in the not so distant future.

Current Progress of Lipid Analysis in Metabolic Diseases by Mass Spectrometry Methods

BACKGROUND

Obesity, insulin resistance, diabetes, and metabolic syndrome are associated with lipid alterations, and they affect the risk of long-term cardiovascular disease. A reliable analytical instrument to detect changes in the composition or structures of lipids and the tools allowing to connect changes in a specific group of lipids with a specific disease and its progress, is constantly lacking. Lipidomics is a new field of medicine based on the research and identification of lipids and lipid metabolites present in human organism. The primary aim of lipidomics is to search for new biomarkers of different diseases, mainly civilization diseases.

OBJECTIVE

We aimed to review studies reporting the application of mass spectrometry for lipid analysis in metabolic diseases.

METHOD

Following an extensive search of peer-reviewed articles on the mass spectrometry analysis of lipids the literature has been discussed in this review article.

RESULTS

The lipid group contains around 1.7 million species; they are totally different, in terms of the length of aliphatic chain, amount of rings, additional functional groups. Some of them are so complex that their complex analyses are a challenge for analysts. Their qualitative and quantitative analysis of is based mainly on mass spectrometry.

CONCLUSION

Mass spectrometry techniques are excellent tools for lipid profiling in complex biological samples and the combination with multivariate statistical analysis enables the identification of potential diagnostic biomarkers.

Developing metabolomics-based bioassessment: crayfish metabolome sensitivity to food and dissolved oxygen stress

There is a need to develop bioassessment tools that can diagnose the effects of individual stressors that can have multiple ecological effects. Using nuclear magnetic resonance (NMR)-based metabolomics, our experiments aimed to identify the sensitivity of metabolites to changes in food availability and dissolved oxygen (DO) concentrations, and compare these results to identify metabolites that may differentiate between the effects of these two stressors. Forty-eight, laboratory-raised, red swamp crayfish (Procambarus clarkii) were randomly assigned and exposed to one of three food availability or DO treatment levels (high, normal, low). Starved crayfish had lower amounts of amino acids than fed crayfish, suggesting catabolic effects of starvation on tail muscle tissue for energy requirements. In contrast, crayfish exposed to hypoxic conditions experienced changes in abundance of metabolites primarily associated with energy metabolism. Tail muscle was the only tissue sensitive to food and DO stress, suggesting the need to select tissues for monitoring appropriately. Our evaluation of environmental metabolomics as a tool for bioassessment indicates that several identified metabolites in crayfish tail muscle may be able to diagnose food and oxygen stress. Further study is required to determine if these metabolic effects are linked with changes of individual fitness and higher levels of biological organization, such as population size.

Metabolomics of Non-muscle Invasive Bladder Cancer: Biomarkers for Early Detection of Bladder Cancer

Background: Clinical outcomes of bladder cancer (BC) are tightly associated with the stage and grade of the initial diagnosis of BC because early detection is clearly important for patients with BC. However, the diagnostic capability of current detection methods, such as urinary cytology, cystoscopy, imageology method, and several urine-based tests, is inadequate for early detection of BC. The objective of our study is to discover novel biomarkers for detecting BC at an early stage, called non-muscle invasive (NMI) BC, using liquid chromatography-high resolution mass spectrometry (LC-HRMS)-based metabolomics.

Methods: First, morning midstream urine samples were collected from healthy adult and NMIBC patients. The LC-HRMS-based metabolomics were applied to distinguish the NMIBC group without hematuria from the controls (gender- and age-matched volunteers with normal clinically healthy index), low-grade NMIBC from the controls, and high-grade from low-grade NMIBC.

Results: A total of 284 subjects were enrolled in our study including 117 healthy adults, 80 NMIBC patients without hematuria, and 87 NMIBC patients with hematuria. The metabolite panel including dopamine 4-sulfate, MG00/1846Z,9Z,12Z,15Z/00, aspartyl-histidine, and tyrosyl-methionine was found in a discovery set, which showed the predictive ability to distinguish the NMIBC group from the control group with an area under the curve (AUC) of 0.838 in an external validation set. The AUC of the panel for low-grade NMIBC samples, which consisted of 3-hydroxy-cis-5-tetradecenoylcarnitine, 6-ketoestriol, beta-cortolone, tetrahydrocorticosterone, and heptylmalonic acid, was 0.899. The sensitivity and specificity were 0.881 and 0.786, respectively. The AUC of the panel for distinction of low-grade NMIBC with and without hematuria against high-grade NMIBC with and without hematuria were 0.827 and 0.755, respectively. In addition, metabolites involved in tryptophan metabolism were upregulated in the urine of high-grade NMIBC patients when compared with low-grade NMIBC patients with the presence or absence of hematuria.

Conclusion: The NMIBC urine metabolic profiling was able to assist in the early detection of BC. Panels of metabolites were discovered to have a potential value for high-grade NMIBC and low-grade NMIBC diagnosis as well as for NMIBC grading distinction.

Characterization of trotter horses urine metabolome by means of proton nuclear magnetic resonance spectroscopy

BACKGROUND

Metabolomics has been recognized as a powerful approach for disease screening. In order to highlight potential health issues in subjects, a key factor is the possibility to compare quantitatively the metabolome of their biofluids with reference values from healthy individuals. Such efforts towards the systematic characterization of the metabolome of biofluids in perfect health conditions, far from concluded for humans, have barely begun on horses.

OBJECTIVES

The present work attempts, for the first time, to give reference quantitative values for the molecules mostly represented in the urine metabolome of horses at rest and under light training, as observable by ¹H-NMR.

METHODS

The metabolome of ten trotter horses, four male and six female, ranging from 3 to 8 years of age, has been observed by ¹H-NMR spectroscopy before and after three training sessions.

RESULTS

We could characterize and quantify 54 molecules in trotter horse urine, originated from diet, protein digestion, energy generation or gut-microbial co-metabolism.

CONCLUSION

We were able to describe how gender, age and exercise affected their concentration, by means of a two steps protocol based on univariate and robust principal component analysis.

Metabolomics studies on corticosterone-induced PC12 cells: A strategy for evaluating an in vitro depression model and revealing the metabolic regulation mechanism

There are three types of differentiated (un-, poorly- and well-differentiated) PC12 cells, which have been widely used as a model system for depression studies after the administration of corticosterone (CORT). In order to investigate the underlying metabolic profiles of CORT-induced PC12 cells and evaluate the suitable differentiated types of PC12 cells for use in depressive studies, proton nuclear magnetic resonance (¹H NMR) metabolomics coupled with network analysis approaches were employed. The results showed that CORT induced metabolic alterations in PC12 cells. There were 8 and 13 common differential metabolites in intracellular and extracellular extracts, respectively, of the three types of differentiated PC12 cells in response to CORT treatment, and the perturbed metabolic pathways were involved in amino acid metabolism, glutathione metabolism, pyruvate metabolism and inositol phosphate metabolism. Eighteen protein targets of depression were identified from the five different metabolic pathways from metabolomics and network analysis among the three types of CORT-induced differentiated PC12 cells, and these proteins were all found in the pathways that were perturbed by CORT treatment of poorly-differentiated PC12 cells. These results may indicate that the metabolism of CORT-induced PC12 cells is similar to the pathogenesis of depression, and poorly-differentiated PC12 cells are the most suitable cells for depressive research among the distinct types of differentiated PC12 cells. Thus, an effective predicative strategy to evaluate the in vitro disease models could be referenced.

Proteo-metabolomics reveals compensation between ischemic and non-injured contralateral kidneys after reperfusion

Ischaemia and reperfusion injury (IRI) is the leading cause of acute kidney injury (AKI), which contributes to high morbidity and mortality rates in a wide range of injuries as well as the development of chronic kidney disease. The cellular and molecular responses of the kidney to IRI are complex and not fully understood. Here, we used an integrated proteomic and metabolomic approach to investigate the effects of IRI on protein abundance and metabolite levels. Rat kidneys were subjected to 45 min of warm ischaemia followed by 4 h and 24 h reperfusion, with contralateral and separate healthy kidneys serving as controls. Kidney tissue proteomics after IRI revealed elevated proteins belonging to the acute phase response, coagulation and complement pathways, and fatty acid (FA) signalling. Metabolic changes were already evident after 4 h reperfusion and showed increased level of glycolysis, lipids and FAs, whilst mitochondrial function and ATP production was impaired after 24 h. This deficit was partially compensated for by the contralateral kidney. Such a metabolic balance counteracts for the developing energy deficit due to reduced mitochondrial function in the injured kidney.

NMR-based metabolomic analysis of the effects of alanyl-glutamine supplementation on C2C12 myoblasts injured by energy deprivation

The dipeptide alanyl-glutamine (Ala-Gln) is a well-known parenteral nutritional supplement. The Ala-Gln supplementation is a potential treatment for muscle-related diseases and injuries. However, molecular mechanisms underlying the polyphenic effects of Ala-Gln supplementation remain elusive. Here, we performed NMR-based metabolomic profiling to analyze the effects of Ala-Gln, and the free alanine (Ala) and glutamine (Gln) supplementations on the mouse myoblast cell line C2C12 injured by glucose and glutamine deprivation. All the three supplementations can promote the differentiation ability of the injured C2C12 cells, while only Ala-Gln supplementation can facilitate the proliferation of the injured cells. Ala-Gln supplementation can partially restore the metabolic profile of C2C12 myoblasts disturbed by glucose and glutamine deprivation, and exhibits more significant effects than Ala and Gln supplementations. Our results suggest that Ala-Gln supplementation can promote MyoD1 protein synthesis, upregulate the muscle ATP-storage phosphocreatine (PCr), maintain TCA cycle anaplerosis, enhance the antioxidant capacity through promoting GSH biosynthesis, and stabilize lipid membranes by suppressing glycerophospholipids metabolism. This work provides new insight into mechanistic understanding of the polyphenic effects of Ala-Gln supplementation on muscle cells injured by energy deprivation.

Quantitative ¹H-NMR Spectroscopy for Profiling Primary Metabolites in Mulberry Leaves

The primary metabolites in aqueous extract of mulberry (Morus alba L.) leaves were characterized by using proton nuclear magnetic resonance (¹H-NMR) spectroscopy. With the convenience of resonance assignment, GABA together with the other 10 primary metabolites was simultaneously identified and quantified in one ¹H-NMR spectrum. In this study, external calibration curves for metabolites were employed to calculate the concentrations of interests. The proposed quantitative approach was demonstrated with good linearity (r² ranged in the interval of 0.9965–0.9999), precision, repeatability, stability (RSD values in the ranges of 0.35–4.89%, 0.77–7.13% and 0.28–2.33%, respectively) and accuracy (recovery rates from 89.2% to 118.5%). The established ¹H-NMR method was then successfully applied to quantify 11 primary metabolites in mulberry leaves from different geographical regions within a rapid analysis time and a simple sample preparation procedure.

Investigation of the urinary metabolic variations and the application in bladder cancer biomarker discovery

Urine metabolomics have been used to identify biomarkers for clinical diseases. However, inter-individual variations and effect factors need to be further evaluated. In our study, we explored the urine metabolome in a cohort of 203 health adults, 6 patients with benign bladder lesions, and 53 patients with bladder cancer (BCa) using liquid chromatography coupled with high resolution mass spectrometry. Inter-individual analysis of both healthy controls and BCa patients showed that the urine metabolome was relatively stable. Further analysis indicated that sex and age affect inter-individual variations in urine metabolome. Metabolic pathways such as tryptophan metabolism, the citrate cycle, and pantothenate and CoA biosynthesis were found to be related to sex and age. To eliminate age and sex interference, additional BCa urine metabolomic biomarkers were explored using age and sex-matched urine samples (Test group: 44 health adults vs. 33 patients with BCa). Metabolic profiling of urine could significantly differentiate the cases with cancer from the controls and high-grade from low-grade BCa. A metabolite panel consisting of trans-2-dodecenoylcarnitine, serinyl-valine, feruloyl-2-hydroxyputrescine, and 3-hydroxynonanoyl carnitine were discovered to have good predictive ability for BCa with an area under the curve (AUC) of 0.956 (cross validation: AUC = 0.924). A panel of indolylacryloylglycine, N₂ -galacturonyl-L-lysine, and aspartyl-glutamate was used to establish a robust model for high- and low-grade BCa distinction with AUC of 0.937 (cross validation: AUC = 0.891). External sample (26 control vs. 20 BCa) validation verified the acceptable accuracy of these models for BCa detection. Our study showed that urinary metabolomics is a useful strategy for differential analysis and biomarker discovery.

Rapid two-dimensional ALSOFAST-HSQC experiment for metabolomics and fluxomics studies: application to a 13C-enriched cancer cell model treated with gold nanoparticles

Isotope labeling enables the use of ¹³C-based metabolomics techniques with strongly improved resolution for a better identification of relevant metabolites and tracing of metabolic fluxes in cell and animal models, as required in fluxomics studies. However, even at high NMR-active isotope abundance, the acquisition of one-dimensional ¹³C and classical two-dimensional ¹H,¹³C-HSQC experiments remains time consuming. With the aim to provide a shorter, more efficient alternative, herein we explored the ALSOFAST-HSQC experiment with its rapid acquisition scheme for the analysis of ¹³C-labeled metabolites in complex biological mixtures. As an initial step, the parameters of the pulse sequence were optimized to take into account the specific characteristics of the complex samples. We then applied the fast two-dimensional experiment to study the effect of different kinds of antioxidant gold nanoparticles on a HeLa cancer cell model grown on ¹³C glucose-enriched medium. As a result, ¹H,¹³C-2D correlations could be obtained in a couple of seconds to few minutes, allowing a simple and reliable identification of various ¹³C-enriched metabolites and the determination of specific variations between the different sample groups. Thus, it was possible to monitor glucose metabolism in the cell model and study the antioxidant effect of the coated gold nanoparticles in detail. Finally, with an experiment time of only half an hour, highly resolved ¹H,¹³C-HSQC spectra using the ALSOFAST-HSQC pulse sequence were acquired, revealing the isotope-position-patterns of the corresponding ¹³C-nuclei from carbon multiplets. Graphical abstract Fast NMR applied to metabolomics and fluxomics studies with gold nanoparticles.

Recommended strategies for spectral processing and post-processing of 1D 1H-NMR data of biofluids with a particular focus on urine

1H NMR spectra from urine can yield information-rich data sets that offer important insights into many biological and biochemical phenomena. However, the quality and utility of these insights can be profoundly affected by how the NMR spectra are processed and interpreted. For instance, if the NMR spectra are incorrectly referenced or inconsistently aligned, the identification of many compounds will be incorrect. If the NMR spectra are mis-phased or if the baseline correction is flawed, the estimated concentrations of many compounds will be systematically biased. Furthermore, because NMR permits the measurement of concentrations spanning up to five orders of magnitude, several problems can arise with data analysis. For instance, signals originating from the most abundant metabolites may prove to be the least biologically relevant while signals arising from the least abundant metabolites may prove to be the most important but hardest to accurately and precisely measure. As a result, a number of data processing techniques such as scaling, transformation and normalization are often required to address these issues. Therefore, proper processing of NMR data is a critical step to correctly extract useful information in any NMR-based metabolomic study. In this review we highlight the significance, advantages and disadvantages of different NMR spectral processing steps that are common to most NMR-based metabolomic studies of urine. These include: chemical shift referencing, phase and baseline correction, spectral alignment, spectral binning, scaling and normalization. We also provide a set of recommendations for best practices regarding spectral and data processing for NMR-based metabolomic studies of biofluids, with a particular focus on urine.

Environmental metabolomics with data science for investigating ecosystem homeostasis

A natural ecosystem can be viewed as the interconnections between complex metabolic reactions and environments. Humans, a part of these ecosystems, and their activities strongly affect the environments. To account for human effects within ecosystems, understanding what benefits humans receive by facilitating the maintenance of environmental homeostasis is important. This review describes recent applications of several NMR approaches to the evaluation of environmental homeostasis by metabolic profiling and data science. The basic NMR strategy used to evaluate homeostasis using big data collection is similar to that used in human health studies. Sophisticated metabolomic approaches (metabolic profiling) are widely reported in the literature. Further challenges include the analysis of complex macromolecular structures, and of the compositions and interactions of plant biomass, soil humic substances, and aqueous particulate organic matter. To support the study of these topics, we also discuss sample preparation techniques and solid-state NMR approaches. Because NMR approaches can produce a number of data with high reproducibility and inter-institution compatibility, further analysis of such data using machine learning approaches is often worthwhile. We also describe methods for data pretreatment in solid-state NMR and for environmental feature extraction from heterogeneously-measured spectroscopic data by machine learning approaches.

Rat Fecal Metabolomics-Based Analysis

Fecal metabolomics-based analysis indisputably constitutes a very useful tool for elucidating the biochemistry of digestion and absorption of the gastrointestinal system. Fecal samples represent the most suitable, non-invasive, specimen for the study of the symbiotic relationship between the host and the intestinal microbiota.It is well established that the balance of the intestinal microbiota changes in response to some stimuli, physiological such as gender, age, diet, exercise and pathological such as gastrointestinal and hepatic disease. Fecal samples have been analyzed using the most widespread analytical techniques, namely, NMR spectroscopy, GC-MS, and LC-MS/MS. Rat fecal sample is a frequently used and particularly useful substrate for metabolomics-based studies in related fields. The complexity and diversity of the nature of fecal samples require careful and skillful handling for the effective quantitative extraction of the metabolites while avoiding their deterioration. Parameters such as the fecal sample weight to extraction solvent volume, the nature and the pH value of the extraction solvent, and the homogenization process are some important factors for the optimal extraction of samples, in order to obtain high-quality metabolic fingerprints, using either untargeted or targeted metabolomics.

Biomarker Discovery in Animal Health and Disease: The Application of Post-Genomic Technologies

The causes of many important diseases in animals are complex and multifactorial, which present unique challenges. Biomarkers indicate the presence or extent of a biological process, which is directly linked to the clinical manifestations and outcome of a particular disease. Identifying biomarkers or biomarker profiles will be an important step towards disease characterization and management of disease in animals. The emergence of post-genomic technologies has led to the development of strategies aimed at identifying specific and sensitive biomarkers from the thousands of molecules present in a tissue or biological fluid. This review will summarize the current developments in biomarker discovery and will focus on the role of transcriptomics, proteomics and metabolomics in biomarker discovery for animal health and disease.

Exploratory metabolomics study of the experimental opisthorchiasis in a laboratory animal model (golden hamster, Mesocricetus auratus)

BACKGROUND

Opisthorchiasis is a parasitic infection caused by the liver flukes of the Opisthorchiidae family. Both experimental and epidemiological data strongly support a role of these parasites in the etiology of the hepatobiliary pathologies and an increased risk of intrahepatic cholangiocarcinoma. Understanding a functional link between the infection and hepatobiliary pathologies requires a detailed description a host-parasite interaction on different levels of biological regulation including the metabolic response on the infection. The last one, however, remains practically undocumented. Here we are describing a host response on Opisthorchiidae infection using a metabolomics approach and present the first exploratory metabolomics study of an experimental model of O. felineus infection.

METHODOLOGY AND PRINCIPAL FINDINGS

We conducted a Nuclear Magnetic Resonance (NMR) based longitudinal metabolomics study involving a cohort of 30 animals with two degrees of infection and a control group. An exploratory analysis shows that the most noticeable trend (30% of total variance) in the data was related to the gender differences. Therefore further analysis was done of each gender group separately applying a multivariate extension of the ANOVA-ASCA (ANOVA simultaneous component analysis). We show that in the males the infection specific time trends are present in the main component (43.5% variance), while in the females it is presented only in the second component and covers 24% of the variance. We have selected and annotated 24 metabolites associated with the observed effects and provided a physiological interpretation of the findings.

CONCLUSIONS

The first exploratory metabolomics study an experimental model of O. felineus infection is presented. Our data show that at early stage of infection a response of an organism unfolds in a gender specific manner. Also main physiological mechanisms affected appear rather nonspecific (a status of the metabolic stress) the data provides a set of the hypothesis for a search of the more specific metabolic markers of the Opisthorchiidae infection.

1H NMR-Based Metabonomic Study of Functional Dyspepsia in Stressed Rats Treated with Chinese Medicine Weikangning

1H NMR-based metabolic profiling combined with multivariate data analysis was used to explore the metabolic phenotype of functional dyspepsia (FD) in stressed rats and evaluate the intervention effects of the Chinese medicine Weikangning (WKN). After a 7-day period of model establishment, a 14-day drug administration schedule was conducted in a WKN-treated group of rats, with the model and normal control groups serving as negative controls. Based on 1H NMR spectra of urine and serum from rats, PCA, PLS-DA, and OPLS-DA were performed to identify changing metabolic profiles. According to the key metabolites determined by OPLS-DA, alterations in energy metabolism, stress-related metabolism, and gut microbiota were found in FD model rats after stress stimulation, and these alterations were restored to normal after WKN administration. This study may provide new insights into the relationship between FD and psychological stress and assist in research into the metabolic mechanisms involved in Chinese medicine.

1H NMR and MVA metabolomic profiles of urines from piglets fed with boluses contaminated with a mixture of five mycotoxins

Metabolic profile of urine from piglets administered with single boluses contaminated with mycotoxin mixture (deoxynivalenol, aflatoxin B1, fumonisin B1, zearalenone, and ochratoxin A) were studied by 1H NMR spectroscopy and chemometrics (PCA, PLS-DA, and OPLS-DA). The mycotoxin levels were close to the established maximum and guidance levels for animal feed (2003/100/EC and 2006/576/EC). Urine samples were obtained from four groups of four piglets before (control, C) or within 24 h (treated, T) after receiving a contaminated boluses with increasing doses of mycotoxins (boluses 1-4). For the two highest dose groups, the urines were collected also after one week of wash out (W). For the two lowest doses groups no significant differences between the C and T samples were observed. By contrast, for the two highest doses groups the T urines separated from the controls for a higher relative content of creatinine, p-cresol glucuronide and phenyl acetyl glycine and lower concentration of betaine and TMAO. Interestingly, a similar profile was found for both W and T urines suggesting, at least for the highest doses used, serious alteration after a single bolus of mycotoxin mixture.

Assessing 2D electrophoretic mobility spectroscopy (2D MOSY) for analytical applications

Electrophoretic displacement of charged entity phase modulates the spectrum acquired in electrophoretic NMR experiments, and this modulation can be presented via 2D FT as 2D mobility spectroscopy (MOSY) spectra. We compare in various mixed solutions the chemical selectivity provided by 2D MOSY spectra with that provided by 2D diffusion-ordered spectroscopy (DOSY) spectra and demonstrate, under the conditions explored, a superior performance of the former method. 2D MOSY compares also favourably with closely related LC-NMR methods. The shape of 2D MOSY spectra in complex mixtures is strongly modulated by the pH of the sample, a feature that has potential for areas such as in drug discovery and metabolomics. Copyright © 2016 The Authors. Magnetic Resonance in Chemistry published by John Wiley & Sons Ltd.

Beyond the paradigm: Combining mass spectrometry and nuclear magnetic resonance for metabolomics

Metabolomics is undergoing tremendous growth and is being employed to solve a diversity of biological problems from environmental issues to the identification of biomarkers for human diseases. Nuclear magnetic resonance (NMR) and mass spectrometry (MS) are the analytical tools that are routinely, but separately, used to obtain metabolomics data sets due to their versatility, accessibility, and unique strengths. NMR requires minimal sample handling without the need for chromatography, is easily quantitative, and provides multiple means of metabolite identification, but is limited to detecting the most abundant metabolites (⩾1μM). Conversely, mass spectrometry has the ability to measure metabolites at very low concentrations (femtomolar to attomolar) and has a higher resolution (∼10³-10⁴) and dynamic range (∼10³-10⁴), but quantitation is a challenge and sample complexity may limit metabolite detection because of ion suppression. Consequently, liquid chromatography (LC) or gas chromatography (GC) is commonly employed in conjunction with MS, but this may lead to other sources of error. As a result, NMR and mass spectrometry are highly complementary, and combining the two techniques is likely to improve the overall quality of a study and enhance the coverage of the metabolome. While the majority of metabolomic studies use a single analytical source, there is a growing appreciation of the inherent value of combining NMR and MS for metabolomics. An overview of the current state of utilizing both NMR and MS for metabolomics will be presented.

Metabolomic approaches in the discovery of potential urinary biomarkers of drug-induced liver injury (DILI)

Drug-induced liver injury (DILI) is a major safety issue during drug development, as well as the most common cause for the withdrawal of drugs from the pharmaceutical market. The identification of DILI biomarkers is a labor-intensive area. Conventional biomarkers are not specific and often only appear at significant levels when liver damage is substantial. Therefore, new biomarkers for early identification of hepatotoxicity during the drug discovery process are needed, thus resulting in lower development costs and safer drugs. In this sense, metabolomics has been increasingly playing an important role in the discovery of biomarkers of liver damage, although the characterization of the mechanisms of toxicity induced by xenobiotics remains a huge challenge. These new-generation biomarkers will offer obvious benefits for the pharmaceutical industry, regulatory agencies, as well as a personalized clinical follow-up of patients, upon validation and translation into clinical practice or approval for routine use. This review describes the current status of the metabolomics applied to the early diagnosis and prognosis of DILI and in the discovery of new potential urinary biomarkers of liver injury.

NMR-based Stable Isotope Resolved Metabolomics in systems biochemistry

Metabolism is the basic activity of live cells, and monitoring the metabolic state provides a dynamic picture of the cells or tissues, and how they respond to external changes, for in disease or treatment with drugs. NMR is an extremely versatile analytical tool that can be applied to a wide range of biochemical problems. Despite its modest sensitivity its versatility make it an ideal tool for analyzing biochemical dynamics both in vitro and in vivo, especially when coupled with its isotope editing capabilities, from which isotope distributions can be readily determined. These are critical for any analyses of flux in live organisms. This review focuses on the utility of NMR spectroscopy in metabolomics, with an emphasis on NMR applications in stable isotope-enriched tracer research for elucidating biochemical pathways and networks with examples from nucleotide biochemistry. The knowledge gained from this area of research provides a ready link to genomic, epigenomic, transcriptomic, and proteomic information to achieve systems biochemical understanding of living cells and organisms.

A 1H-NMR based metabolomics study of the intervention effect of mangiferin on hyperlipidemia hamsters induced by a high-fat diet

Mangiferin ameliorated hyperlipidemia by intervening in some major metabolic pathways.

Early preterm nutrition and the urinary metabolome in young adult life: follow-up of a randomised controlled trial

OBJECTIVE

We aimed to test the hypothesis that early diet programmes the metabolic profile of young adults born preterm.

DESIGN

We analysed banked urine samples obtained at a 20-year follow-up visit from adults that had participated as neonates in controlled trials involving randomisation within 48 hours of birth to feeds of preterm formula (PTF), banked breast milk (BBM) or term formula (TF) for 1 month postnatally.

MAIN OUTCOME MEASURES

We performed proton nuclear magnetic resonance spectroscopy, analysing spectra by dietary group and sex. Orthogonal projections to latent structure discriminant analyses was used to model class differences and identify metabolites contributing to the differences between groups. Additionally, spectra were correlated with birth weight, gestational age and weight z score at 2 weeks of age.

RESULTS

Of the original number of 926 trial participants, urine samples were available from 197 (21%) healthy young adults (42% men) born preterm (mean 30.7±2.8 weeks) and randomised to BBM (n=55; 28 men), TF (n=48; 14 men) and PTF (n=93; 40 men). We found no significant differences in urinary spectra between dietary groups including when stratified by sex. Correlation analysis revealed a weak association between metabolic profile and gestational age that was lost on controlling for ethanol excretion.

CONCLUSIONS

We found no evidence that dietary exposures in the neonatal period influence the metabolic phenotype in young adult life.