Nuclear Magnetic Resonance Metabolomics Research Articles

Quality evaluation of different varieties of dry red wine based on nuclear magnetic resonance metabolomics

The metabolites that provide the aroma and flavor to wine are the products of several influences, such as grape cultivar, geographic location and associated environmental features, viticultural practices, and vinification techniques, which are central to production protocols, quality evaluation and development of wine regions. Accordingly, we initiated the requisite studies to investigate the differences in the dry red wine metabolites of different grape varieties. The proton-nuclear magnetic resonance technique (1H-NMR) combined with multivariate statistical analysis was used to investigate the changes of metabolite levels in Cabernet Sauvignon, Merlot and Cabernet Gernischt dry red wines vinified in Changli, Hebei province, China, in 2017. The results showed that the types of metabolites in different varieties of dry red wines were similar, but the content was significantly different. The main contributors to the differences in Cabernet Sauvignon, Merlot and Cabernet Gernischt dry red wines were ethyl acetate, lactic acid, alanine, succinic acid, proline, malic acid, and gallic acid, indicating 1H-NMR method combined with multivariate statistical analysis can distinguish these three types of dry red wines from each other. It provides a benchmark for further comparative study on wine quality and the verification of wine authenticity.

Metabolic effects of PCSK9 inhibition with Evolocumab in subjects with elevated Lp(a)

BackgroundEpidemiological studies substantiated that subjects with elevated lipoprotein(a) [Lp(a)] have a markedly increased cardiovascular risk. Inhibition of proprotein convertase subtilisin/kexin type 9 (PCSK9) lowers both LDL cholesterol (LDL-C) as well as Lp(a), albeit modestly. Effects of PCSK9 inhibition on circulating metabolites such as lipoprotein subclasses, amino acids and fatty acids remain to be characterized.MethodsWe performed nuclear magnetic resonance (NMR) metabolomics on plasma samples derived from 30 individuals with elevated Lp(a) (> 150 mg/dL). The 30 participants were randomly assigned into two groups, placebo (N = 14) and evolocumab (N = 16). We assessed the effect of 16 weeks of evolocumab 420 mg Q4W treatment on circulating metabolites by running lognormal regression analyses, and compared this to placebo. Subsequently, we assessed the interrelationship between Lp(a) and 14 lipoprotein subclasses in response to treatment with evolocumab, by running multilevel multivariate regression analyses.ResultsOn average, evolocumab treatment for 16 weeks resulted in a 17% (95% credible interval: 8 to 26%, P < 0.001) reduction of circulating Lp(a), coupled with substantial reduction of VLDL, IDL and LDL particles as well as their lipid contents. Interestingly, increasing concentrations of baseline Lp(a) were associated with larger reduction in triglyceride-rich VLDL particles after evolocumab treatment.ConclusionsInhibition of PCSK9 with evolocumab markedly reduced VLDL particle concentrations in addition to lowering LDL-C. The extent of reduction in VLDL particles depended on the baseline level of Lp(a). Our findings suggest a marked effect of evolocumab on VLDL metabolism in subjects with elevated Lp(a).Trial registrationClinical trial registration information is registered at ClinicalTrials.gov on April 14, 2016 with the registration number NCT02729025.

Exploring feature selection of St John's wort grown under different light spectra using 1 H-NMR spectroscopy.

Nuclear magnetic resonance (NMR) spectroscopy combined with multivariate statistical analysis can provide tools to help detect differences in plant chemistry when grown under varying conditions. Hypericum perforatum, or Saint John's wort, plants are a suitable model to explore methods of discrimination between early stage plants grown in different conditions. The purpose of this work was to develop a method for identifying differences in chemical profiles between young Hypericum perforatum plants grown under different lighting conditions. Cuttings were grown for 3 weeks under different light conditions. Plant extracts were prepared in MeOD-d4 and analysed by 1 H-NMR. A multivariate analysis method of the NMR data was developed in an effort to determine variations in chemical profiles. The method identified specific metabolites as drivers of difference between the plants grown under different light conditions. STOCSY (statistical total correlation spectroscopy) and quantification of highlighted metabolites supported the findings of the multivariate analysis. Glutamine, sucrose and fructose were found to be chemical markers of light quality in this study. NMR metabolomics using a medium field instrument could find differences in plant chemistry when grown in different conditions. This method could easily be extended to benchtop instruments and be used for crop monitoring and growth condition optimisation.

Optimization of Synovial Fluid Collection and Processing for NMR Metabolomics and LC-MS/MS Proteomics.

Synovial fluid (SF) is of great interest for the investigation of orthopedic pathologies, as it is in close proximity to various tissues that are primarily altered during these disease processes and can be collected using minimally invasive protocols. Multi-“omic” approaches are commonplace, although little consideration is often given for multiple analysis techniques at sample collection. Nuclear magnetic resonance (NMR) metabolomics and liquid chromatography tandem mass spectrometry (LC-MS/MS) proteomics are two complementary techniques particularly suited to the study of SF. However, currently there are no agreed upon standard protocols that are published for SF collection and processing for use with NMR metabolomic analysis. Furthermore, the large protein concentration dynamic range present within SF can mask the detection of lower abundance proteins in proteomics. While combinational ligand libraries (ProteoMiner columns) have been developed to reduce this dynamic range, their reproducibility when used in conjunction with SF, or on-bead protein digestion protocols, has yet to be investigated. Here we employ optimized protocols for the collection, processing, and storage of SF for NMR metabolite analysis and LC-MS/MS proteome analysis, including a Lys-C endopeptidase digestion step prior to tryptic digestion, which increased the number of protein identifications and improved reproducibility for on-bead ProteoMiner digestion.

Nuclear Magnetic Resonance Metabolomics Biomarkers for Identifying High Risk Patients with Extranodal Extension in Oral Squamous Cell Carcinoma.

Extranodal extension (ENE) is an independent adverse prognostic factor in oral squamous cell carcinoma (OSCC), and is difficult to identify preoperatively. We aimed to discover biomarkers for high risk patients with ENE. Tandem tissue, plasma, and urine samples of 110 patients with OSCC were investigated through 600-MHz nuclear magnetic resonance (NMR) metabolomics analysis. We found that the levels of creatine, creatine phosphate, glycine, and tyramine in plasma significantly decreased in stage IV ENE positive OSCC compared with stage IV ENE negative OSCC. To understand the underlying mechanism behind the alteration of plasma metabolites, our tissue analysis revealed that the carnitine level significantly increased in tumors but significantly decreased in the adjacent normal tissue in advanced stage OSCC, in addition to decreased levels of alanine and pyruvate in tumor tissues. The global metabolomics analysis on tumor tissues also showed that stage IV tumors with an ENE positive status demonstrated higher levels of aspartate, butyrate, carnitine, glutamate, glutathione, glycine, glycolate, guanosine, and sucrose but lower levels of alanine, choline, glucose, isoleucine, lactate, leucine, myo-inositol, O-acetylcholine, oxypurinol, phenylalanine, pyruvate, succinate, tyrosine, valine, and xanthine than tumors with an ENE negative status. We concluded that metabolomics alterations in tumor tissues correspond to an increase in the tumor stage and are detectable in plasma samples. Metabolomic alterations of OSCC can serve as potential diagnostic markers and predictors of ENE in patients with stage IV OSCC.

Systems Metabolic Alteration in a Semi-Dwarf Rice Mutant Induced by OsCYP96B4 Gene Mutation.

Dwarfism and semi-dwarfism are among the most valuable agronomic traits in crop breeding, which were adopted by the “Green Revolution”. Previously, we reported a novel semi-dwarf rice mutant (oscyp96b4) derived from the insertion of a single copy of Dissociator (Ds) transposon into the gene OsCYP96B4. However, the systems metabolic effect of the mutation is not well understood, which is important for understanding the gene function and developing new semi-dwarf mutants. Here, the metabolic phenotypes in the semi-dwarf mutant (M) and ectopic expression (ECE) rice line were compared to the wild-type (WT) rice, by using nuclear magnetic resonance (NMR) metabolomics and quantitative real-time polymerase chain reaction (qRT-PCR). Compared with WT, ECE of the OsCYP96B4 gene resulted in significant increase of γ-aminobutyrate (GABA), glutamine, and alanine, but significant decrease of glutamate, aromatic and branched-chain amino acids, and some other amino acids. The ECE caused significant increase of monosaccharides (glucose, fructose), but significant decrease of disaccharide (sucrose); induced significant changes of metabolites involved in choline metabolism (phosphocholine, ethanolamine) and nucleotide metabolism (adenosine, adenosine monophosphate, uridine). These metabolic profile alterations were accompanied with changes in the gene expression levels of some related enzymes, involved in GABA shunt, glutamate and glutamine metabolism, choline metabolism, sucrose metabolism, glycolysis/gluconeogenesis pathway, tricarboxylic acid (TCA) cycle, nucleotide metabolism, and shikimate-mediated secondary metabolism. The semi-dwarf mutant showed corresponding but less pronounced changes, especially in the gene expression levels. It indicates that OsCYP96B4 gene mutation in rice causes significant alteration in amino acid metabolism, carbohydrate metabolism, nucleotide metabolism, and shikimate-mediated secondary metabolism. The present study will provide essential information for the OsCYP96B4 gene function analysis and may serve as valuable reference data for the development of new semi-dwarf mutants.

Proton Nuclear Magnetic Resonance Metabolomics Corroborates Serine Hydroxymethyltransferase as the Primary Target of 2-Aminoacrylate in a ridA Mutant of Salmonella enterica.

The reactive intermediate deaminase RidA (EC 3.5.99.10) is conserved across all domains of life and deaminates reactive enamine species. When Salmonella enterica ridA mutants are grown in minimal medium, 2-aminoacrylate (2AA) accumulates, damages several pyridoxal 5'-phosphate (PLP)-dependent enzymes, and elicits an observable growth defect. Genetic studies suggested that damage to serine hydroxymethyltransferase (GlyA), and the resultant depletion of 5,10-methelenetetrahydrofolate (5,10-mTHF), was responsible for the observed growth defect. However, the downstream metabolic consequence from GlyA damage by 2AA remains relatively unexplored. This study sought to use untargeted proton nuclear magnetic resonance (1H NMR) metabolomics to determine whether the metabolic state of an S. enterica ridA mutant was accurately reflected by characterizing growth phenotypes. The data supported the conclusion that metabolic changes in a ridA mutant were due to the IlvA-dependent generation of 2AA, and that the majority of these changes were a consequence of damage to GlyA. While many of the metabolic differences for a ridA mutant could be explained, changes in some metabolites were not easily modeled, suggesting that additional levels of metabolic complexity remain to be unraveled.IMPORTANCE The accumulation of the reactive enamine intermediate 2-aminoacrylate (2AA) elicits global metabolic stress in many prokaryotes and eukaryotes by simultaneously damaging multiple pyridoxal 5'-phosphate (PLP)-dependent enzymes. This work employed 1H NMR to expand our understanding of the consequence(s) of 2AA stress on metabolite pools and effectively identify the metabolic changes stemming from one damaged target: GlyA. This study shows that nutrient supplementation during 1H NMR metabolomics experiments can disentangle complex metabolic outcomes stemming from a general metabolic stress. Metabolomics shows great potential to complement classical reductionist approaches to cost-effectively accelerate the rate of progress in expanding our global understanding of metabolic network structure and physiology. To that end, this work demonstrates the utility in implementing nutrient supplementation and genetic perturbation into metabolomics workflows as a means to connect metabolic outputs to physiological phenomena and establish causal relationships.

1H NMR-Based Metabolomics Approach in Investigating the Chemical Profile, Antioxidant and Anti-Inflammatory Activities of Gynura procumbens and Cleome gynandra.

Gynura procumbens and Cleome gynandra are two herbs commonly used in Malaysia to treat various ailments and are also consumed as salads (ulam) and vegetables. The present study aims to evaluate the relationship between the chemical compositions of both herbs and their antioxidant and anti-inflammatory properties using nuclear magnetic resonance (NMR) metabolomics approach, which is being reported for the first time. Different ethanolic extracts of both herbs were tested for DPPH scavenging and inhibition of nitric oxide (NO) via RAW 264.7 macrophage cell induction. Principal component analysis (PCA) revealed a good separation between the extracts and the corresponding metabolites identified via 1H NMR spectroscopy. The 100% ethanolic extract from both herbs and 20% ethanolic extract of C. gynandra were found to have the best antioxidant and anti-inflammatory activities. Kaempferol, quercetin, caffeoylquinic, dicaffeoylquinic acids, gallic acid, mallic acid, citric acid, phenylalanine, and choline are among the metabolites that contributed to bioactivities. The partial least square (PLS) model for both herbs have an overall acceptable goodness of fit and predictive power, which further strengthens the validity of this study. The present study provides a preliminary reference for the selection of optimum extract and will shed some light on the potential use of G. procumbens and C. gynandra as a phytomedicinal preparation.

Sensory Assessment of Fish and Chicken Protein Hydrolysates. Evaluation of NMR Metabolomics Profiling as a New Prediction Tool.

Nuclear magnetic resonance (NMR) metabolomics profiling was evaluated as a new tool in sensory assessment of protein hydrolysates. Hydrolysates were produced on the basis of different raw materials (cod, salmon, and chicken), enzymes (Food Pro PNL and Bromelain), and hydrolysis time (10 and 50 min). The influence of raw material and hydrolysis parameters on sensory attributes was determined by traditional descriptive sensory analysis and 1H NMR spectroscopy. The raw material had a major influence on the attribute intensity and metabolite variation, followed by enzyme and hydrolysis time. However, the formation of bitter taste was not affected by the raw material. Partial least-squares regression (PLSR) on 1H NMR and sensory data provided good models (Q2 = 0.55-0.89) for 11 of the 17 evaluated attributes, including bitterness. Significant metabolite-attribute associations were identified. The study confirms the potential prediction of the sensory properties of protein hydrolysates from cod, salmon, and chicken based on 1H NMR metabolomics profiling.

Circulating Fatty Acids and Risk of Coronary Heart Disease and Stroke: Individual Participant Data Meta-Analysis in Up to 16126 Participants.

BackgroundWe aimed at investigating the association of circulating fatty acids with coronary heart disease (CHD) and stroke risk.Methods and ResultsWe conducted an individual‐participant data meta‐analysis of 5 UK‐based cohorts and 1 matched case‐control study. Fatty acids (ie, omega‐3 docosahexaenoic acid, omega‐6 linoleic acid, monounsaturated and saturated fatty acids) were measured at baseline using an automated high‐throughput serum nuclear magnetic resonance metabolomics platform. Data from 3022 incident CHD cases (13 104 controls) and 1606 incident stroke cases (13 369 controls) were included. Logistic regression was used to model the relation between fatty acids and odds of CHD and stroke, adjusting for demographic and lifestyle variables only (ie, minimally adjusted model) or with further adjustment for other fatty acids (ie, fully adjusted model). Although circulating docosahexaenoic acid, but not linoleic acid, was related to lower CHD risk in the fully adjusted model (odds ratio, 0.85; 95% CI, 0.76–0.95 per standard unit of docosahexaenoic acid), there was evidence of high between‐study heterogeneity and effect modification by study design. Stroke risk was consistently lower with increasing circulating linoleic acid (odds ratio for fully adjusted model, 0.82; 95% CI, 0.75–0.90). Circulating monounsaturated fatty acids were associated with higher CHD risk across all models and with stroke risk in the fully adjusted model (odds ratio, 1.22; 95% CI, 1.03–1.44). Saturated fatty acids were not related to increased CHD risk in the fully adjusted model (odds ratio, 0.94; 95% CI, 0.82–1.09), or stroke risk.ConclusionsWe found consistent evidence that linoleic acid was associated with decreased risk of stroke and that monounsaturated fatty acids were associated with increased risk of CHD. The different pattern between CHD and stroke in terms of fatty acids risk profile suggests future studies should be cautious about using composite events. Different study designs are needed to assess which, if any, of the associations observed is causal.

Signature Mapping (SigMa): An efficient approach for processing complex human urine 1H NMR metabolomics data

Proton Nuclear Magnetic Resonance (NMR) spectroscopic analysis of urine generates rich but complex spectra. Retrieving metabolite information from such spectra is challenging due to signal overlapping, chemical shift changes, and large concentration variations of complex urine metabolome. This study demonstrates a new method, Signature Mapping (SigMa), for the rapid and efficient conversion of raw urine NMR spectra into an informative metabolite table. The principle behind SigMa relies on a division of the urine NMR spectra into Signature Signals (SS), Signals of Unknown spin Systems (SUS) and bins of complex unresolved regions (BINS). The method allows simultaneous detection of urinary metabolites in large NMR metabolomics studies using a SigMa chemical shift library and a new automatic peak picking algorithm. For quantification of SS and SUS SigMa uses multivariate curve resolution, while the unresolved inter-SS spectral regions are binned (BINS). SigMa is tested on three human urine 1H-NMR datasets including spiking experiments, and has proven to be extraordinarily efficient, quantitatively reliable and robust.

Early Human-Milk Metabolome in Cases of Intrauterine Growth-Restricted and Macrosomic Infants.

Abnormal fetal growth is associated with short-term and long-term metabolic dysregulation and susceptibility to obesity-related disorders. Maternal milk, the ideal source of infantile nutrition, protects from metabolic diseases in adulthood. By applying nuclear magnetic resonance (NMR) metabolomics, this study investigated the metabolic profile of early human milk/colostrum (EHM/C) at the extremes of fetal-growth conditions, which could affect its nutritional value. From 98mothers delivering 60 appropriate-for-gestational-age (AGA), 19 large-for-gestational-age (LGA), and 19 intrauterine growth-restricted (IUGR) full-term neonates, milk samples collected on the third to fourth day post partum were examined by NMR spectroscopy. Multivariate data analysis elicited information from NMR spectra and probed to metabolic signatures of EHM/C. LGA and IUGR EHM/C samples depicted increased content in lactose, citric acid, choline, phosphocholine, and N-acetylglutamine. AGA samples exhibited increased isoleucine and valine. Metabolic pathways involved were valine, leucine/isoleucine biosynthesis and degradation, glycerophospholipid metabolism, aminoacyl-transfer RNA biosynthesis, and citrate cycle. Orthogonal projections to latent structures discriminant analysis models were validated. This holistic metabolomics study framed an increased content of certain essential nutrients in EHM/C samples following the birth of LGA and IUGR infants prone to short- and long-term metabolic disorders, thus stressing additional benefits of early breastfeeding. Assessing the metabolic profile of EHΜ/C enables evaluation of its nutrition value, adjusted to fetal growth, and introduction of appropriate dietary interventions.

Untargeted metabolic fingerprinting reveals impact of growth stage and location on composition of sea buckthorn (Hippophaë rhamnoides) leaves.

Sea buckthorn (Hippophaë rhamnoides) is increasingly cultivated to produce raw materials for food and nutraceuticals. There is little knowledge on composition of sea buckthorn leaves (SBLs) and the key factors influencing the composition. This research aims to unravel the metabolic profile of SBLs and the effects of cultivar, location and stage of growth, and climatic conditions on the metabolic profile of SBLs. Leaves of two sea buckthorn cultivars grown in the south and north of Finland during two consecutive growth seasons were studied using untargeted nuclear magnetic resonance (NMR) metabolomics. The highest variance in the metabolic profile was linked to the growth stage, wherein leaves from the first 7 weeks of harvest were characterized with higher abundance of polyphenols, while relatively higher abundance of carbohydrates and sugars was observed in the later weeks. The growth location attributed for the second highest variation, wherein the north-south comparison identified fatty acids and sugars as discriminatory metabolites, and the potential association of metabolome to natural abiotic stressors was revealed. An inverse correlation between carbohydrate/sugar content as well as fatty acids of higher carbon chain length with the temperature variables was evident. The supervised chemometric models with high sensitivity and specificity classified and predicted the samples based on growth stage and location, and cultivar. Nontargeted NMR-metabolomics revealed the metabolic profile of SBLs and their variation associated with various biotic and abiotic factors. Cultivar and growth stage are key factors to consider when harvesting SBLs for use in food and nutraceuticals. PRACTICAL APPLICATION: Globally, sea buckthorn cultivation has been rapidly increasing due to the known health-promoting benefits of the berries and leaves of the plant. The current research obtained new comprehensive information on the compositional profile of sea buckthorn leaves as well as the impact of major contributory factors, such as cultivars, the advancement of growth stage, geographical location, and weather parameters. The findings of this research provide new knowledge and guidance for plant breeding, cultivation and commercial utilization of sea buckthorn leaves as raw materials for food, feed, and nutraceuticals.

1 H-NMR metabolomics profiling of recombinant tobacco plants holding a promoter of a sesquiterpene cyclase.

Nicotiana tabacum is a plant model intensively used in the bio-engineering pharmaceutical industry as a platform to produce drugs and therapeutic agents. Currently, no information regarding the non-targeted metabolome of transgenic tobacco containing recombinant regulatory sequences is available. To compare the proton nuclear magnetic resonance (1 H-NMR) metabolomics profiling of a recombinant Nicotiana tabacum strain containing a promoter of a sesquiterpene cyclase from Capsicum annuum driving GUS expression, versus wild-type samples. Methodology The non-targeted 1 H-NMR metabolome was obtained and processed by principal component analysis (PCA) and orthogonal projection to latent structures discriminant analysis (OPLS-DA). The differential metabolites were quantified by quantitative NMR. PCA and OPLS-DA revealed 37 metabolites including 16 discriminant compounds for transgenic samples. Ethanol (0.4 mg g-1 ), the main differential compound, was exclusively detected in transgenic tobacco; however, high levels of formate (0.28 mg g-1 ) and acetate (0.3 mg g-1 ) were simultaneously observed in the same group of samples. Cembratriene-4,6-diol, an antitumour and neuroprotective compound, and capsidiol, a known phytoalexin, increased by about 30% in transgenic samples. In addition, the endogenous levels of the antioxidant caffeoylquinic acid isomers increased by 50% in comparison to those of wild-type tobaccos. Our results support the occurrence of metabolic differences between wild type and transgenic tobacco containing a promoter of a Capsicum sesquiterpene cyclase gene. Interestingly, the recombinant transgenic strain studied accumulated high amounts of added value compounds with biological activity.

A059 Metabolomics and a Breath Sensor Identify Acetone as a Biomarker for Heart Failure

Metabolomics delivers more biological and clinical insight than targeted investigations. We applied metabolomics to patients with heart failure (HF) with reduced ejection fraction (HFrEF). 46 patients with HFrEF and 20 controls underwent metabolomic profiling, including liquid/gas chromatography mass spectrometry (LC-MS/GC-MS), nuclear magnetic resonance (NMR) metabolomics and solid-phase microextraction (SPME) volatilomics in plasma and urine. HFrEF was defined using left ventricular global longitudal strain (GLS) < 18%, ejection fraction < 50% and NTproBNP ≥ 35 pmol/L. A low cost consumer breath acetone (BrACE) sensor validated SPME results in 69 patients. 34 metabolites were identified by GCMS, 33 by LCMS and 2 volatiles by SPME (acetone, 2-pentanone in plasma and urine). Alanine, aspartate and glutamate, citric acid cycle, arginine biosynthesis, glyoxylate and dicarboxylate metabolism were altered in HFrEF. Plasma acetone correlated with NT-proBNP (r = 0.59, 95% CI 0.4 to 0.7), triacylglycerol (55:9), 2-oxovaleric and cis-aconitic acid, involved with ketone metabolism and mitochondrial energetics. BrACE > 1.5 ppm discriminated HF from other cardiac pathology (AUC 0.88, 95% CI 0.77 to 0.99, P < 0.0001). Breath acetone was detectable in HFrEF patients using a consumer sensor ($1/test) and although not cardiac specific, discriminated HF from other cardiac pathology.

Intact NMR spectroscopy: slow high-resolution magic angle spinning chemical shift imaging.

High-Resolution Magic-Angle Spinning Chemical Shift Imaging (HR-MAS CSI) has recently been explored for nuclear magnetic resonance (NMR) metabolomics and shows considerable promise in organism research. This is due to its ability to offer a supplemental dimension - spatial metabolic distribution - for profiling. However, HR-MAS CSI suffers from the large centrifugal stress exerted on the sample, which inevitably hinders the metabolic assessment. Herein, a slow sample spinning strategy was implemented and evaluated. The results demonstrate its potential as a highly informative profiling approach for intact specimens, with high quality data and feasibility.

Analysis of NMR Metabolomics Data.

In this chapter, we summarize data preprocessing and data analysis strategies used for analysis of NMR data for metabolomics studies. Metabolomics consists of the analysis of the low molecular weight compounds in cells, tissues, or biological fluids, and has been used to reveal biomarkers for early disease detection and diagnosis, to monitor interventions, and to provide information on pathway perturbations to inform mechanisms and identifying targets. Metabolic profiling (also termed metabotyping) involves the analysis of hundreds to thousands of molecules using mainly state-of-the-art mass spectrometry (MS) and nuclear magnetic resonance (NMR)spectroscopy technologies. While NMR is less sensitive than mass spectrometry, NMR does provide a wealth of complex and information rich metabolite data. NMR data together with the use of conventional statistics, modeling methods, and bioinformatics tools reveals biomarker and mechanistic information. A typical NMR spectrum, with up to 64k data points, of a complex biological fluid or an extract of cells and tissues consists of thousands of sharp signals that are mainly derived from small molecules. In addition, a number of advanced NMR spectroscopic methods are available for extracting information on high molecular weight compounds such as lipids or lipoproteins. There are numerous data preprocessing, data reduction, and analysis methods developed and evolving in the field of NMR metabolomics. Our goal is to provide an extensive summary of NMR data preprocessing and analysis strategies by providing examples and open source and commercially available analysis software and bioinformatics tools.

Metabolic Age Based on the BBMRI-NL 1H-NMR Metabolomics Repository as Biomarker of Age-related Disease.

The blood metabolome incorporates cues from the environment and the host's genetic background, potentially offering a holistic view of an individual's health status. We have compiled a vast resource of proton nuclear magnetic resonance metabolomics and phenotypic data encompassing over 25 000 samples derived from 26 community and hospital-based cohorts. Using this resource, we constructed a metabolomics-based age predictor (metaboAge) to calculate an individual's biological age. Exploration in independent cohorts demonstrates that being judged older by one's metabolome, as compared with one's chronological age, confers an increased risk on future cardiovascular disease, mortality, and functionality in older individuals. A web-based tool for calculating metaboAge (metaboage.researchlumc.nl) allows easy incorporation in other epidemiological studies. Access to data can be requested at bbmri.nl/samples-images-data. In summary, we present a vast resource of metabolomics data and illustrate its merit by constructing a metabolomics-based score for biological age that captures aspects of current and future cardiometabolic health.

Integrated Metabolomics and Transcriptomics Suggest the Global Metabolic Response to 2-Aminoacrylate Stress in Salmonella enterica.

In Salmonella enterica, 2-aminoacrylate (2AA) is a reactive enamine intermediate generated during a number of biochemical reactions. When the 2-iminobutanoate/2-iminopropanoate deaminase (RidA; EC: 3.5.99.10) is eliminated, 2AA accumulates and inhibits the activity of multiple pyridoxal 5’-phosphate(PLP)-dependent enzymes. In this study, untargeted proton nuclear magnetic resonance (1H NMR) metabolomics and transcriptomics data were used to uncover the global metabolic response of S. enterica to the accumulation of 2AA. The data showed that elimination of RidA perturbed folate and branched chain amino acid metabolism. Many of the resulting perturbations were consistent with the known effect of 2AA stress, while other results suggested additional potential enzyme targets of 2AA-dependent damage. The majority of transcriptional and metabolic changes appeared to be the consequence of downstream effects on the metabolic network, since they were not directly attributable to a PLP-dependent enzyme. In total, the results highlighted the complexity of changes stemming from multiple perturbations of the metabolic network, and suggested hypotheses that will be valuable in future studies of the RidA paradigm of endogenous 2AA stress.

Copper modulates sex-specific fructose hepatoxicity in nonalcoholic fatty liver disease (NALFD) Wistar rat models

This study aimed to characterize the impact of dietary copper on the biochemical and hepatic metabolite changes associated with fructose toxicity in a Wistar rat model of fructose-induced liver disease. Twenty-four male and 24 female, 6-week-old, Wister rats were separated into four experimental dietary treatment groups (6 males and 6 females per group), as follows: (1) a control diet: containing no fructose with adequate copper (i.e., CuA/0% Fruct); (2) a diet regimen identical to the control and supplemented with 30% w/v fructose in the animals' drinking water (CuA/30% Fruct); (3) a diet identical to the control diet but deficient in copper content (CuD/0% Fruct) and (4) a diet identical to the control diet but deficient in copper content and supplemented with 30% w/v fructose in the drinking water (CuD/30% Fruct). The animals were fed the four diet regimens for 5 weeks, followed by euthanization and assessment of histology, elemental profiles and identification and quantitation of liver metabolites. Results from 1H nuclear magnetic resonance metabolomics revealed mechanistic insights into copper modulation of fructose hepatotoxicity through identification of distinct metabolic phenotypes that were highly correlated with diet and sex. This study also identified previously unknown sex-specific responses to both fructose supplementation and restricted copper intake, while the presence of adequate dietary copper promoted most pronounced fructose-induced metabolite changes.