International NMR-based environmental metabolomics intercomparison exercise

Transcriptome analysis reveals the role of polysaccharide biosynthesis in the detoxification of Dendrobium nobile under zinc stress

Plants can bind excessive heavy metals by synthesizing compounds to alleviate the harm caused by heavy metals. To reveal the mechanism by which Dendrobium nobile alleviates zinc stress, metabolome combined transcriptome analysis was used in this research. The results showed that zinc was mainly enriched in the roots and leaves and the biomass of the roots and leaves of D. nobile decreased significantly by 18.21 % and 49.22 % (P < 0.05) compared to the control (CK), respectively. Meanwhile, the contents of nonprotein thiol(NPT), glutathione(GSH), and phytochelatins (PCs) in the roots were significantly increased by 48.8 %, 78.3 %, and 45.4 % compared to CK, respectively. Through TEM testing, it was found that D. nobile exhibited toxic symptoms. Metabolome analysis showed that the metabolites of D. nobile under zinc stress were mainly enriched in biosynthesis of other secondary metabolites and carbohydrate metabolism. Nova-seq results identified 1202 differentially expressed genes(DEGs), of which 603 were upregulated and 599 were downregulated. Through GO and KEGG annotation analysis of these DEGs, it was found that PMR6 and PECS-2.1, SS1 and GLU3 genes were significantly upregulated, leading to an increase in the biosynthesis of xylan, pectin, starch and other polysaccharides in D. nobile. These polysaccharides can form a "Polysaccharide-Zn" with excess zinc. Meanwhile, the GSTs in glutathione metabolism were significantly upregulated, leading to a significant increase in the content of NPT, GSH, and PCs. These zinc complexes were transported to vacuoles through ABC transporters for compartmentalization, effectively alleviating the damage of zinc. The results can provide new insights for phytoremediation and quality assurance of medicinal D. nobile.

Serum metabolomic profiling identifies potential biomarkers in arthritis in older adults: an exploratory study

BACKGROUND

Seronegative elderly-onset rheumatoid arthritis (EORA)^neg and polymyalgia rheumatica (PMR) have similar clinical characteristics making them difficult to distinguish based on clinical features. We hypothesized that the study of serum metabolome could identify potential biomarkers of PMR vs. EORA^neg.

METHODS

Arthritis in older adults (ARTIEL) is an observational prospective cohort with patients older than 60 years of age with newly diagnosed arthritis. Patients' blood samples were compared at baseline with 18 controls. A thorough clinical examination was conducted. A Bruker Avance 600 MHz spectrometer was used to acquire Nuclear Magnetic Resonance (NMR) spectra of serum samples. Chenomx NMR suite 8.5 was used for metabolite identification and quantification.Student t-test, one-way ANOVA, binary linear regression and ROC curve, Pearson's correlation along with pathway analyses were conducted.

RESULTS

Twenty-eight patients were diagnosed with EORA^neg and 20 with PMR. EORA^neg patients had a mean disease activity score (DAS)-Erythrocyte Sedimentation Rate (ESR) of 6.21 ± 1.00. All PMR patients reported shoulder pain, and 90% reported pelvic pain. Fifty-eight polar metabolites were identified. Of these, 3-hydroxybutyrate, acetate, glucose, glycine, lactate, and o-acetylcholine (o-ACh), were significantly different between groups. Of interest, IL-6 correlated with different metabolites in PMR and EORA^neg suggesting different inflammatory activated pathways. Finally, lactate, o-ACh, taurine, and sex (female) were identified as distinguishable factors of PMR from EORA^neg with a sensitivity of 90%, specificity of 92.3%, and an AUC of 0.925 (p < 0.001).

CONCLUSION

These results suggest that EORA^neg and PMR have different serum metabolomic profiles that might be related to their pathobiology and can be used as biomarker to discriminate between both diseases.

Cross-Platform Comparison of Amino Acid Metabolic Profiling in Three Model Organisms Used in Environmental Metabolomics

Environmental metabolomics is a promising approach to study pollutant impacts to target organisms in both terrestrial and aquatic environments. To this end, both nuclear magnetic resonance (NMR)- and mass spectrometry (MS)-based methods are used to profile amino acids in different environmental metabolomic studies. However, these two methods have not been compared directly which is an important consideration for broader comparisons in the environmental metabolomics field. We compared the quantification of 18 amino acids in the tissue extracts of Daphnia magna, a common model organism used in both ecotoxicology and ecology, using both 1H NMR spectroscopy and liquid chromatography with tandem MS (LC-MS/MS). 1H NMR quantification of amino acids agreed with the LC-MS/MS quantification for 17 of 18 amino acids measured. We also tested both quantitative methods in a D. magna sub-lethal exposure study to copper and lithium. Again, both NMR and LC-MS/MS measurements showed agreement. We extended our analyses with extracts from the earthworm Eisenia fetida and the plant model Nicotiana tabacum. The concentrations of amino acids by both 1H NMR and LC-MS/MS, agreed and demonstrated the robustness of both techniques for quantitative metabolomics. These findings demonstrate the compatibility of these two analytical platforms for amino acid profiling in environmentally relevant model organisms and emphasizes that data from either method is robust for comparisons across studies to further build the knowledge base related to pollutant exposure impacts and toxic responses of diverse environmental organisms.

Review on in vivo profiling of drug metabolites with LC-MS/MS in the past decade

Metabolite profiling is an indispensable part of drug discovery and development, enabling a comprehensive understanding of the drug's metabolic behavior. Liquid chromatography-mass spectrometry facilitates metabolite profiling by reducing sample complexity and providing high sensitivity. This review discusses the in vivo metabolite profiling involving LC-MS/MS and the utilization of QTOF, QQQ mass analyzers with a particular emphasis on a mass filter. Further, a summary of sample extraction procedures in biological matrices such as plasma, urine, feces, serum and hair as in vivo samples are outlined. toward the end, we present 15 case studies in biological matrices and their LC-MS/MS conditions to understand the metabolic disposition.

NMR spectroscopy of wastewater: A review, case study, and future potential

NMR spectroscopy is arguably the most powerful tool for the study of molecular structures and interactions, and is increasingly being applied to environmental research, such as the study of wastewater. With over 97% of the planet's water being saltwater, and two thirds of freshwater being frozen in the ice caps and glaciers, there is a significant need to maintain and reuse the remaining 1%, which is a precious resource, critical to the sustainability of most life on Earth. Sanitation and reutilization of wastewater is an important method of water conservation, especially in arid regions, making the understanding of wastewater itself, and of its treatment processes, a highly relevant area of environmental research. Here, the benefits, challenges and subtleties of using NMR spectroscopy for the analysis of wastewater are considered. First, the techniques available to overcome the specific challenges arising from the nature of wastewater (which is a complex and dilute matrix), including an examination of sample preparation and NMR techniques (such as solvent suppression), in both the solid and solution states, are discussed. Then, the arsenal of available NMR techniques for both structure elucidation (e.g., heteronuclear, multidimensional NMR, homonuclear scalar coupling-based experiments) and the study of intermolecular interactions (e.g., diffusion, nuclear Overhauser and saturation transfer-based techniques) in wastewater are examined. Examples of wastewater NMR studies from the literature are reviewed and potential areas for future research are identified. Organized by nucleus, this review includes the common heteronuclei (¹³C, ¹⁵N, ¹⁹F, ³¹P, ²⁹Si) as well as other environmentally relevant nuclei and metals such as ²⁷Al, ⁵¹V, ²⁰⁷Pb and ¹¹³Cd, among others. Further, the potential of additional NMR methods such as comprehensive multiphase NMR, NMR microscopy and hyphenated techniques (for example, LC-SPE-NMR-MS) for advancing the current understanding of wastewater are discussed. In addition, a case study that combines natural abundance (i.e. non-concentrated), targeted and non-targeted NMR to characterize wastewater, along with in vivo based NMR to understand its toxicity, is included. The study demonstrates that, when applied comprehensively, NMR can provide unique insights into not just the structure, but also potential impacts, of wastewater and wastewater treatment processes. Finally, low-field NMR, which holds considerable future potential for on-site wastewater monitoring, is briefly discussed. In summary, NMR spectroscopy is one of the most versatile tools in modern science, with abilities to study all phases (gases, liquids, gels and solids), chemical structures, interactions, interfaces, toxicity and much more. The authors hope this review will inspire more scientists to embrace NMR, given its huge potential for both wastewater analysis in particular and environmental research in general.

You Are What You Eat: Application of Metabolomics Approaches to Advance Nutrition Research

A healthy condition is defined by complex human metabolic pathways that only function properly when fully satisfied by nutritional inputs. Poor nutritional intakes are associated with a number of metabolic diseases, such as diabetes, obesity, atherosclerosis, hypertension, and osteoporosis. In recent years, nutrition science has undergone an extraordinary transformation driven by the development of innovative software and analytical platforms. However, the complexity and variety of the chemical components present in different food types, and the diversity of interactions in the biochemical networks and biological systems, makes nutrition research a complicated field. Metabolomics science is an "-omic", joining proteomics, transcriptomics, and genomics in affording a global understanding of biological systems. In this review, we present the main metabolomics approaches, and highlight the applications and the potential for metabolomics approaches in advancing nutritional food research.

Method comparison of HPLC-ninhydrin-photometry and UHPLC-PITC-tandem mass spectrometry for serum amino acid analyses in patients with complex congenital heart disease and controls

INTRODUCTION

Metabolomics studies are not routine when quantifying amino acids (AA) in congenital heart disease (CHD).

OBJECTIVES

Comparative analysis of 24 AA in serum by traditional high-performance liquid chromatography (HPLC) based on ion exchange and ninhydrin derivatisation followed by photometry (PM) with ultra-high-performance liquid chromatography and phenylisothiocyanate derivatisation followed by tandem mass spectrometry (TMS); interpretation of findings in CHD patients and controls.

METHODS

PM: Sample analysis as above (total run time, ~ 119 min). TMS: Sample analysis by AbsoluteIDQ® p180 kit assay (BIOCRATES Life Sciences AG, Innsbruck, Austria), which employs PITC derivatisation; separation of analytes on a Waters Acquity UHPLC BEH18 C18 reversed-phase column, using water and acetonitrile with 0.1% formic acid as the mobile phases; and quantification on a Triple-Stage Quadrupole tandem mass spectrometer (Thermo Fisher Scientific, Waltham, MA) with electrospray ionisation in the presence of internal standards (total run time, ~ 8 min). Calculation of coefficients of variation (CV) (for precision), intra- and interday accuracies, limits of detection (LOD), limits of quantification (LOQ), and mean concentrations.

RESULTS

Both methods yielded acceptable results with regard to precision (CV < 10% PM, < 20% TMS), accuracies (< 10% PM, < 34% TMS), LOD, and LOQ. For both Fontan patients and controls AA concentrations differed significantly between methods, but patterns yielded overall were parallel.

CONCLUSION

Serum AA concentrations differ with analytical methods but both methods are suitable for AA pattern recognition. TMS is a time-saving alternative to traditional PM under physiological conditions as well as in patients with CHD.

TRIAL REGISTRATION NUMBER

ClinicalTrials.gov Identifier NCT03886935, date of registration March 27th, 2019 (retrospectively registered).

NMR-based metabolomic analysis for the effects of Huiyang Shengji extract on rat diabetic skin ulcers

ETHNOPHARMACOLOGICAL RELEVANCE

Huiyang Shengji formula (HSF) is a compound Chinese herbal medicine prescription, and has long been used for treating chronic non-healing wounds.

AIM OF THE STUDY

The purpose of this study was to provide new insight into molecular mechanisms of healing effects of the HSF treatments.

MATERIALS AND METHODS

We established a rat diabetic skin ulcer (DSU) model, and assessed healing effects of four HSF treatments on DSUs by calculating wound healing rates and immunohistochemical detection of the expressions of angiogenesis-related factors in the model rats (Mod) relative to normal rats (Nor), including Huiyang extract (HE), Shengji extract (SE), Huiyang Shengji extract (HSE) and HSE associated with acupuncture (Ac-HSE). We then performed NMR-based metabolomic analyses on skin tissues of the Nor, Mod, HSE-treated, Ac-HSE-treated rats to address metabolic mechanisms underlying these effects.

RESULTS

These treatments up-regulated expressions of two angiogenesis-related factors VEGF and CD31, and improved efficacy of healing DSUs, in which HSE and Ac-HSE exhibited the most significant effects. Compared with Mod, HSE and Ac-HSE groups shared four characteristic metabolites (lactate, histidine, succinate and acetate) and four significantly altered metabolic pathways with Nor. Both HSE and Ac-HSE treatments could partly reverse the metabolically disordered pathological state of DSUs to the normal state. They might improve wound healing through promoting glucose metabolism, BCAAs metabolism, and enhancing antioxidant capacity and angiogenesis in DSU tissues. Ac-HSE significantly enhanced wound healing rates compared to HSE, potentially owing to significant capacities of enhancing anti-oxidation and angiogenesis and interfering three more metabolic pathways.

CONCLUSIONS

This work provides a mechanistic understanding of the healing effects of the HSE and Ac-HSE treatments on DSUs, is of benefit to improvements of the HSF treatments for clinically healing chronic non-healing wounds.

Ecometabolomics for a Better Understanding of Plant Responses and Acclimation to Abiotic Factors Linked to Global Change

The number of ecometabolomic studies, which use metabolomic analyses to disentangle organisms' metabolic responses and acclimation to a changing environment, has grown exponentially in recent years. Here, we review the results and conclusions of ecometabolomic studies on the impacts of four main drivers of global change (increasing frequencies of drought episodes, heat stress, increasing atmospheric carbon dioxide (CO2) concentrations and increasing nitrogen (N) loads) on plant metabolism. Ecometabolomic studies of drought effects confirmed findings of previous target studies, in which most changes in metabolism are characterized by increased concentrations of soluble sugars and carbohydrate derivatives and frequently also by elevated concentrations of free amino acids. Secondary metabolites, especially flavonoids and terpenes, also commonly exhibited increased concentrations when drought intensified. Under heat and increasing N loads, soluble amino acids derived from glutamate and glutamine were the most responsive metabolites. Foliar metabolic responses to elevated atmospheric CO2 concentrations were dominated by greater production of monosaccharides and associated synthesis of secondary metabolites, such as terpenes, rather than secondary metabolites synthesized along longer sugar pathways involving N-rich precursor molecules, such as those formed from cyclic amino acids and along the shikimate pathway. We suggest that breeding for crop genotypes tolerant to drought and heat stress should be based on their capacity to increase the concentrations of C-rich compounds more than the concentrations of smaller N-rich molecules, such as amino acids. This could facilitate rapid and efficient stress response by reducing protein catabolism without compromising enzymatic capacity or increasing the requirement for re-transcription and de novo biosynthesis of proteins.

A community-built calibration system: The case study of quantification of metabolites in grape juice by qNMR spectroscopy

Nuclear Magnetic Resonance (NMR) is an analytical technique extensively used in almost every chemical laboratory for structural identification. This technique provides statistically equivalent signals in spite of using spectrometer with different hardware features and is successfully used for the traceability and quantification of analytes in food samples. Nevertheless, to date only a few internationally agreed guidelines have been reported on the use of NMR for quantitative analysis. The main goal of the present study is to provide a methodological pipeline to assess the reproducibility of NMR data produced for a given matrix by spectrometers from different manufacturers, with different magnetic field strengths, age and hardware configurations. The results have been analyzed through a sequence of chemometric tests to generate a community-built calibration system which was used to verify the performance of the spectrometers and the reproducibility of the predicted sample concentrations.

Metabolome response to anthropogenic contamination on microalgae: a review

BACKGROUND

Microalgae play a key role in ecosystems and are widely used in ecological status assessment. Research focusing on such organisms is then well developed and essential. Anyway, approaches for a better comprehension of their metabolome's response towards anthropogenic stressors are only emerging.

AIM OF REVIEW

This review presents the biochemical responses of various microalgae species towards several contaminants including metals and chemicals as pesticides or industrial compounds. We aim to provide a comprehensive and up-to-date overview of analytical approaches deciphering anthropogenic contaminants impact on microalgae metabolome dynamics, in order to bring out relevant biochemical markers that could be used for risk assessment.

KEY SCIENTIFIC CONCEPTS OF REVIEW

Studies to date on ecotoxicological metabolomics on microalgae are highly heterogeneous in both analytical techniques and resulting metabolite identification. There is a real need for studies using complementary approaches to determine biomarkers usable for ecological risk assessment.

Metabolic adaptation to feed restriction on the green sturgeon (Acipenser medirostris) fingerlings

Food restriction may cause severe biological effects on wildlife and lead to population decline and extinction. The objective of the current study was to examine the metabolic effects on green sturgeon in response to feed restriction. Green sturgeon fingerlings were fed for two weeks at 12.5, 25, 50 and 100% of the optimum feeding rate (OFR), which corresponded to 0.25, 0.50, 1.00, and 2.00% body weight per day. We characterized the changes in hydrophilic and hydrophobic metabolites from extracts of muscle, liver, and kidney using nuclear magnetic resonance spectroscopy followed by multivariate statistical analysis. The results of principal component analysis (PCA) score plots from the analyses of hydrophilic metabolites showed that they exhibited a greater response to feed restriction than hydrophobic metabolites. In general, the hydrophilic metabolites in tissues from fish fed ≦25% of the OFR were separated from those fed 100% of the OFR in the PCA score plots. Among the three types of tissues examined, the overall metabolite changes showed a greater response to feed restriction in kidney tissue than in liver or muscle tissues. Numerous glucogenic amino acids in muscle and most amino acids in the kidney were decreased under feed restriction conditions. A significant decrease in ketone bodies (3-hydroxyisobutyrate) was observed in the muscle. Most fatty acids except for glycerol, phospholipid and cholesterol in the liver and kidney tissues were decreased under feed restriction conditions. Creatine phosphate, taurine and glycine were also significantly increased in tissues under feed restriction conditions. In conclusion, this study suggests that the manipulation of feed restriction under the current conditions perturbed metabolites related to energy metabolism, osmolality regulation, and antioxidation capacity in the sturgeon.

Dose-dependent effects induced by cadmium in polychaete Perinereis aibuhitensis

Cadmium is a known metal contaminant in the Bohai Sea. In this study, the dose-dependent responses induced by Cd were characterized in marine polychaete Perinereis aibuhitensis using the endpoints, including activities of enzymes, expression levels of stress-responsive genes and metabolic responses. Both enzyme activities and gene expression levels exhibited the hormetic effects induced by Cd in P. aibuhitensis, as shown by the typical U-shaped or inverted U-shaped response profiles. The highest concentration (1280 µg/L) of Cd exposure induced obvious oxidative stresses. NMR-based metabolomics revealed that Cd induced both linear dose-dependent effects (69.13% of the total variation) and a relatively slight hormesis (5.54% of the total variation) in energy metabolism in P. aibuhitensis at metabolite level. In details, Cd exposures linearly reduced the consumption of amino acids and enhanced the consumption of glucose for energy supply, resulting in elevated contents of amino acids and depleted contents of glucose. Additionally, Cd treatments induced hormesis in the conversion of ATP hydrolysis to AMP. This work suggested that the hormetic effects should be considered in the ecological risk assessment for the environmental pollutants.

Processing and Analysis of Untargeted Multicohort NMR Data

NMR data from large studies combining multiple cohorts is becoming common in large-scale metabolomics. The data size and combination of cohorts with diverse properties leads to special problems for data processing and analysis. These include alignment, normalization, detection and removal of outliers, presence of strong correlations, and the identification of unknowns. Nonetheless, these challenges can be addressed with suitable algorithms and techniques, leading to enhanced data sets ripe for further data mining.

Hepatic metabolite profiling of polychlorinated biphenyl (PCB)-resistant and sensitive populations of Atlantic killifish (Fundulus heteroclitus)

Atlantic killifish inhabiting polluted sites along the east coast of the U.S. have evolved resistance to toxic effects of contaminants. One such contaminated site is the Acushnet River estuary, near New Bedford Harbor (NBH), Massachusetts, which is characterized by very high PCB concentrations in the sediments and in the tissues of resident killifish. Though killifish at this site appear to be thriving, the metabolic costs of survival in a highly contaminated environment are not well understood. In this study we compared the hepatic metabolite profiles of resistant (NBH) and sensitive populations (Scorton Creek (SC), Sandwich, MA) using a targeted metabolomics approach in which polar metabolites were extracted from adult fish livers and quantified. Our results revealed differences in the levels of several metabolites between fish from the two sites. The majority of these metabolites are associated with one-carbon metabolism, an important pathway that supports multiple physiological processes including DNA and protein methylation, nucleic acid biosynthesis and amino acid metabolism. We measured the gene expression of DNA methylation (DNA methyltransferase 1, dnmt1) and demethylation genes (Ten-Eleven Translocation (TET) genes) in the two populations, and observed lower levels of dnmt1 and higher levels of TET gene expression in the NBH livers, suggesting possible differences in DNA methylation profiles. Consistent with this, the two populations differed significantly in the levels of 5-methylcytosine and 5-hydroxymethylcytosine nucleotides. Overall, our results suggest that the unique hepatic metabolite signatures observed in NBH and SC reflect the adaptive mechanisms for survival in their respective habitats.

Evaluation of Daphnia magna metabolic responses to organic contaminant exposure with and without dissolved organic matter using 1H nuclear magnetic resonance (NMR)-based metabolomics

Previous studies have shown that contaminant toxicity to target organisms is altered by the presence of dissolved organic matter (DOM). Contaminants can bind to DOM and this may alter the bioavailability and subsequent toxicity of the contaminants. However, molecular-level techniques are needed to more closely evaluate the impact of DOM on the sub-lethal biochemical responses to emerging contaminants. To investigate how DOM may alter the metabolic response to organic contaminant exposure, ¹H nuclear magnetic resonance (NMR)-based metabolomics was used to investigate how the metabolome of Daphnia magna changes when Suwannee River DOM (5 mg organic carbon/L) is included in the acute exposure of four contaminants with varying hydrophobicity. Sub-lethal concentrations of the hydrophobic contaminant 17α-ethynylestradiol (EE2), the relatively more polar compounds carbamazepine and imidacloprid, or the anionic contaminant perfluorooctane sulfonate (PFOS) were used. A 48-h exposure to DOM alone had a minor impact on the metabolome of D. magna. There were significant increases in amino acids from EE2 exposure which were reduced in the presence of DOM, suggesting that DOM may alleviate the sub-lethal metabolic response from EE2 exposure through sorption and a reduction in freely dissolved EE2. The metabolome was relatively unaltered with exposure to carbamazepine and imidacloprid in the presence of DOM which is likely because these contaminants are water soluble and did not strongly interact with DOM. PFOS exposure resulted in a more significant metabolic response with DOM suggesting that DOM enhanced the uptake and bioavailability of PFOS in D. magna. As such, the presence of DOM should be considered when determining sensitive molecular-level changes in organisms to sub-lethal organic contaminant exposure.

Serum metabolomic profiling predicts synovial gene expression in rheumatoid arthritis

Background

Metabolomics is an emerging field of biomedical research that may offer a better understanding of the mechanisms of underlying conditions including inflammatory arthritis. Perturbations caused by inflamed synovial tissue can lead to correlated changes in concentrations of certain metabolites in the synovium and thereby function as potential biomarkers in blood. Here, we explore the hypothesis of whether characterization of patients’ metabolomic profiles in blood, utilizing ¹H-nuclear magnetic resonance (NMR), predicts synovial marker profiling in rheumatoid arthritis (RA).

Methods

Nineteen active, seropositive patients with RA, on concomitant methotrexate, were studied. One of the involved joints was a knee or a wrist appropriate for arthroscopy. A Bruker Avance 700 MHz spectrometer was used to acquire NMR spectra of serum samples. Gene expression in synovial tissue obtained by arthroscopy was analyzed by real-time PCR. Data processing and statistical analysis were performed in Python and SPSS.

Results

Analysis of the relationships between each synovial marker-metabolite pair using linear regression and controlling for age and gender revealed significant clustering within the data. We observed an association of serine/glycine/phenylalanine metabolism and aminoacyl-tRNA biosynthesis with lymphoid cell gene signature. Alanine/aspartate/glutamate metabolism and choline-derived metabolites correlated with TNF-α synovial expression. Circulating ketone bodies were associated with gene expression of synovial metalloproteinases. Discriminant analysis identified serum metabolites that classified patients according to their synovial marker levels.

Conclusion

The relationship between serum metabolite profiles and synovial biomarker profiling suggests that NMR may be a promising tool for predicting specific pathogenic pathways in the inflamed synovium of patients with RA.

Electronic supplementary material

The online version of this article (10.1186/s13075-018-1655-3) contains supplementary material, which is available to authorized users.

Classification of samples from NMR-based metabolomics using principal components analysis and partial least squares with uncertainty estimation

Recent progress in metabolomics has been aided by the development of analysis techniques such as gas and liquid chromatography coupled with mass spectrometry (GC-MS and LC-MS) and nuclear magnetic resonance (NMR) spectroscopy. The vast quantities of data produced by these techniques has resulted in an increase in the use of machine algorithms that can aid in the interpretation of this data, such as principal components analysis (PCA) and partial least squares (PLS). Techniques such as these can be applied to biomarker discovery, interlaboratory comparison, and clinical diagnoses. However, there is a lingering question whether the results of these studies can be applied to broader sets of clinical data, usually taken from different data sources. In this work, we address this question by creating a metabolomics workflow that combines a previously published consensus analysis procedure ( https://doi.org/10.1016/j.chemolab.2016.12.010 ) with PCA and PLS models using uncertainty analysis based on bootstrapping. This workflow is applied to NMR data that come from an interlaboratory comparison study using synthetic and biologically obtained metabolite mixtures. The consensus analysis identifies trusted laboratories, whose data are used to create classification models that are more reliable than without. With uncertainty analysis, the reliability of the classification can be rigorously quantified, both for data from the original set and from new data that the model is analyzing. Graphical abstract ᅟ.

Morin as a Preservative for Delaying Senescence of Banana

Banana is a climacteric fruit with desirable palatability and high nutritional value. It ripens rapidly accompanied with metabolite changes during postharvest storage. In this work, morin was applied to treat banana to delay senescence. Nuclear magnetic resonance (NMR) spectroscopy was used to monitor the changes of metabolite composition and levels in banana. The results showed that morin significantly delayed the changes of color and firmness. 1D and 2D NMR spectra reflected that the levels and composition of metabolites were changed with the senescence initiation. The principal component analysis revealed that the first principal components responsible for banana senescence were carbohydrates, amino acids, lipids and phenolics. Morin treatment delayed the transformation of starch to glucose, fructose and sucrose, accelerated the accumulations of alanine and γ-Amino-butyrate (GABA), postponed the generations of valine and l-aspartic acid, suppressed the degradation of saponin a. It indicated that morin was effective in delaying banana senescence.

The 1H-NMR-based metabolite profile of acute alcohol consumption: A metabolomics intervention study

Metabolomics studies of disease conditions related to chronic alcohol consumption provide compelling evidence of several perturbed metabolic pathways underlying the pathophysiology of alcoholism. The objective of the present study was to utilize proton nuclear magnetic resonance (1H-NMR) spectroscopy metabolomics to study the holistic metabolic consequences of acute alcohol consumption in humans. The experimental design was a cross-over intervention study which included a number of substances to be consumed-alcohol, a nicotinamide adenine dinucleotide (NAD) supplement, and a benzoic acid-containing flavoured water vehicle. The experimental subjects-24 healthy, moderate-drinking young men-each provided six hourly-collected urine samples for analysis. Complete data sets were obtained from 20 of the subjects and used for data generation, analysis and interpretation. The results from the NMR approach produced complex spectral data, which could be resolved sufficiently through the application of a combination of univariate and multivariate methods of statistical analysis. The metabolite profiles resulting from acute alcohol consumption indicated that alcohol-induced NAD+ depletion, and the production of an excessive amount of reducing equivalents, greatly perturbed the hepatocyte redox homeostasis, resulting in essentially three major metabolic disturbances-up-regulated lactic acid metabolism, down-regulated purine catabolism and osmoregulation. Of these, the urinary excretion of the osmolyte sorbitol proved to be novel, and suggests hepatocyte swelling due to ethanol influx following acute alcohol consumption. Time-dependent metabolomics investigations, using designed interventions, provide a way of interpreting the variation induced by the different factors of a designed experiment, thereby also giving methodological significance to this study. The outcomes of this approach have the potential to significantly advance our understanding of the serious impact of the pathophysiological perturbations which arise from the consumption of a single, large dose of alcohol-a simulation of a widespread, and mostly naive, social practice.

Application of kernel principal component analysis and computational machine learning to exploration of metabolites strongly associated with diet

Computer-based technological innovation provides advancements in sophisticated and diverse analytical instruments, enabling massive amounts of data collection with relative ease. This is accompanied by a fast-growing demand for technological progress in data mining methods for analysis of big data derived from chemical and biological systems. From this perspective, use of a general “linear” multivariate analysis alone limits interpretations due to “non-linear” variations in metabolic data from living organisms. Here we describe a kernel principal component analysis (KPCA)-incorporated analytical approach for extracting useful information from metabolic profiling data. To overcome the limitation of important variable (metabolite) determinations, we incorporated a random forest conditional variable importance measure into our KPCA-based analytical approach to demonstrate the relative importance of metabolites. Using a market basket analysis, hippurate, the most important variable detected in the importance measure, was associated with high levels of some vitamins and minerals present in foods eaten the previous day, suggesting a relationship between increased hippurate and intake of a wide variety of vegetables and fruits. Therefore, the KPCA-incorporated analytical approach described herein enabled us to capture input–output responses, and should be useful not only for metabolic profiling but also for profiling in other areas of biological and environmental systems.

Analysis of earthworm sublethal toxic responses to atrazine exposure using 1 H nuclear magnetic resonance (NMR)-based metabolomics

Atrazine toxicity to earthworms is still not fully understood, particularly at sublethal concentrations. Because of the ubiquity of atrazine in the environment, it is imperative to understand the impacts of atrazine presence to soil-dwelling organisms. To examine this in detail, we used ¹ H nuclear magnetic resonance (NMR)-based metabolomics to elucidate earthworm (Eisenia fetida) responses after 48 h of atrazine exposure in contact tests. Earthworms were exposed to 4 sublethal concentrations of 362.4, 181.2, 90.6, and 45.3 ng/cm² , which correspond to 1/8th, 1/16th, 1/32nd, and 1/64th of the median lethal concentration (LC50) values, respectively. After exposure, polar metabolites were isolated from earthworm tissues and analyzed using ¹ H NMR spectroscopy. Sublethal atrazine exposure induced a nonmonotonic response with respect to exposure concentration and caused an overall suppression in earthworm metabolism. Maltose, fumarate, malate, threonine/lactate, adenosine-5'-triphosphate (ATP), betaine, scyllo-inositol, glutamate, arginine, and glutamine were the metabolites identified as most sensitive to atrazine exposure. These observed fluctuations in the metabolic profile suggest that atrazine reduced ATP synthesis and negatively impacted the health of earthworms after acute sublethal exposure. Our study also demonstrates the utility of NMR-based metabolomics for the basic assessment of sublethal toxicity, which can then be used for more targeted approaches with other molecular techniques. Environ Toxicol Chem 2018;37:473-480. © 2017 SETAC.

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.

Environmental Nuclear Magnetic Resonance Spectroscopy: An Overview and a Primer

NMR spectroscopy is a versatile tool for the study of structure and interactions in environmental media such as air, soil, and water as well as monitoring the metabolic responses of living organisms to an ever changing environment. Part review, part perspective, and part tutorial, this Feature is aimed at nonspecialists who are interested in learning more about the potential and impact of NMR spectroscopy in environmental research.

Omics tools: New challenges in aquatic nanotoxicology?

In recent years, the implication of genomics into ecotoxicological studies has been studied closely to allow a better understanding of organism's responses to environmental contaminants including engineering nanomaterials (ENMs). ENMs are increasingly produced for various applications including cosmetics, electronics, sports equipment, biomedicine and agriculture. Because of their small size, ENMs possess chemical or physical characteristics improved compared to the corresponding macro-sized material. As their application expend, the release of manufactured ENMs into the environment is likely to increase and concern over impacts for the aquatic ecosystem is growing. Several studies reported deleterious effect of ENMs to aquatic organisms, but there is little information about the molecular mechanisms of toxicity. The development of ecotoxicogenomic approaches will improve the characterization of cellular and molecular modes of action of ENMs to aquatic organisms and allow a better prediction of contaminants toxicity. This paper presents an overview of transciptomic/proteomic studies in freshwater and marine organisms exposed to ENMs. Overall, induction of gene expression in relations to defense mechanisms, immune responses, growth and reproduction were measured after ENMs exposures of organisms, but with different patterns depending on exposure duration and concentrations used. In addition, some studies reported a positive correlation between gene expression and cellular modifications, but not at the individual level.

Bacterial Substrate Transformation Tracked by Stable-Isotope-Guided NMR Metabolomics: Application in a Natural Aquatic Microbial Community

The transformation of organic substrates by heterotrophic bacteria in aquatic environments constitutes one of the key processes in global material cycles. The development of procedures that would enable us to track the wide range of organic compounds transformed by aquatic bacteria would greatly improve our understanding of material cycles. In this study, we examined the applicability of nuclear magnetic resonance spectroscopy coupled with stable-isotope labeling to the investigation of metabolite transformation in a natural aquatic bacterial community. The addition of a model substrate (¹³C₆–glucose) to a coastal seawater sample and subsequent incubation resulted in the detection of >200 peaks and the assignment of 22 metabolites from various chemical classes, including amino acids, dipeptides, organic acids, nucleosides, nucleobases, and amino alcohols, which had been identified as transformed from the ¹³C₆–glucose. Additional experiments revealed large variability in metabolite transformation and the key compounds, showing the bacterial accumulation of glutamate over the incubation period, and that of 3-hydroxybutyrate with increasing concentrations of ¹³C₆–glucose added. These results suggest the potential ability of our approach to track substrate transformation in aquatic bacterial communities. Further applications of this procedure may provide substantial insights into the metabolite dynamics in aquatic environments.

Harmonizing lipidomics: NIST interlaboratory comparison exercise for lipidomics using SRM 1950-Metabolites in Frozen Human Plasma

As the lipidomics field continues to advance, self-evaluation within the community is critical. Here, we performed an interlaboratory comparison exercise for lipidomics using Standard Reference Material (SRM) 1950-Metabolites in Frozen Human Plasma, a commercially available reference material. The interlaboratory study comprised 31 diverse laboratories, with each laboratory using a different lipidomics workflow. A total of 1,527 unique lipids were measured across all laboratories and consensus location estimates and associated uncertainties were determined for 339 of these lipids measured at the sum composition level by five or more participating laboratories. These evaluated lipids detected in SRM 1950 serve as community-wide benchmarks for intra- and interlaboratory quality control and method validation. These analyses were performed using nonstandardized laboratory-independent workflows. The consensus locations were also compared with a previous examination of SRM 1950 by the LIPID MAPS consortium. While the central theme of the interlaboratory study was to provide values to help harmonize lipids, lipid mediators, and precursor measurements across the community, it was also initiated to stimulate a discussion regarding areas in need of improvement.

NMR-based metabolomic study on the toxicological effects of pesticide, diazinon on adaptation to sea water by endangered Persian sturgeon, Acipenser persicus fingerlings

NMR-based metabolomics was applied to explore metabolic impacts of diazinon on sea water adaptation of Persian sturgeon fingerlings, Acipenser persicus. Fingerlings were exposed to sub-lethal concentrations of diazinon in freshwater (FW) for 96 h (short-term trial) and 12 days (long-term trial) and then exposed in brackish water (BW) (12 mg L^-1 salinity) for 24 h. After 96 h and 12 days exposure in FW, identified metabolites (amino acids, osmolytes, energy metabolites) showed different change-patterns compared to control group (P < 0.05) as follow: (A) short-term trial: higher plasma levels of glucose, lactate (in all diazinon-exposed fish), acetate and acetoacetate (in 0.9 mg L^-1diazinon treatment); lower levels of creatine (in all diazinon-exposed fish), trimethylamine-N-oxide, choline, taurine, betaine, N,N-dimethylglycine and almost all amino acids in fish exposed to high concentrations of diazinon (0.54 and 0.9 mg L^-1 diazinon). (B) Long-term trial: higher plasma levels of lipid oxidation metabolites and almost all amino acids in fish exposed to 0.54 and 0.9 mg L^-1 diazinon; lower levels of creatine, trimethylamine-N-oxide, N,N-dimethylglycine, betaine, choline (in all diazinon-exposed fish), glucose (in 0.54 and 0.9 mg L^-1diazinon treatments) and taurine (in 0.9 mg L^-1 diazinon treatment). When fish were exposed in BW for 24 h, the plasma levels of osmolytes decreased significantly in almost all experimental groups of short-term and long-term trial (P < 0.05). In short-term trial, the plasma levels of glucose in all groups and lactate in 0.18 and 0.54 mg L^-1 diazinon treatments increased after salinity challenge (P < 0.05). However, a significant decrease was observed in lactate levels in 0.9 mg L^-1 diazinon treatment (P < 0.05). Also, the plasma levels of amino acids decreased mostly in fish of control group than exposed fish (P < 0.05). The plasma glycerol concentration showed a significant decrease only in fish of 0.54 mg L^-1 diazinon treatment (P < 0.05). In long term trial, the energetic metabolites (acetate, acetoacetate, glycerol) showed significant increases mostly in fish exposed to high concentrations of diazinon (P < 0.05). Phosphocreatine was detected only in groups exposed to 0.54 and 0.9 mg L^-1 diazinon. Some amino acids decreased in control and diazinon-exposed groups while glycine (in control and 0.18 mg L^-1 diazinon treatment), glutamine and alanine (in 0.9 mg L^-1 diazinon treatment) elevated significantly after 24 h acclimation in BW (P < 0.05). Our results may help to understand the effects of pesticides on fish osmoregulation from a metabolic approach.

Metabolomics Analysis of Effects of Commercial Soy-based Protein Products in Red Drum (Sciaenops ocellatus)

We investigated the metabolic effects of four different commercial soy-based protein products on red drum fish (Sciaenops ocellatus) using nuclear magnetic resonance (NMR) spectroscopy-based metabolomics along with unsupervised principal component analysis (PCA) to evaluate metabolic profiles in liver, muscle, and plasma tissues. Specifically, during a 12 week feeding trial, juvenile red drum maintained in an indoor recirculating aquaculture system were fed four different commercially available soy formulations, containing the same amount of crude protein, and two reference diets as performance controls: a 60% soybean meal diet that had been used in a previous trial in our lab and a natural diet. Red drum liver, muscle, and plasma tissues were sampled at multiple time points to provide a more accurate snapshot of specific metabolic states during the grow-out. PCA score plots derived from NMR spectroscopy data sets showed significant differences between fish fed the natural diet and the soy-based diets, in both liver and muscle tissues. While red drum tolerated the inclusion of soy with good feed conversion ratios, a comparison to fish fed the natural diet revealed that the soy-fed fish in this study displayed a distinct metabolic signature characterized by increased protein and lipid catabolism, suggesting an energetic imbalance. Furthermore, among the soy-based formulations, one diet showed a more pronounced catabolic signature.

A scoring metric for multivariate data for reproducibility analysis using chemometric methods

Process quality control and reproducibility in emerging measurement fields such as metabolomics is normally assured by interlaboratory comparison testing. As a part of this testing process, spectral features from a spectroscopic method such as nuclear magnetic resonance (NMR) spectroscopy are attributed to particular analytes within a mixture, and it is the metabolite concentrations that are returned for comparison between laboratories. However, data quality may also be assessed directly by using binned spectral data before the time-consuming identification and quantification. Use of the binned spectra has some advantages, including preserving information about trace constituents and enabling identification of process difficulties. In this paper, we demonstrate the use of binned NMR spectra to conduct a detailed interlaboratory comparison and composition analysis. Spectra of synthetic and biologically-obtained metabolite mixtures, taken from a previous interlaboratory study, are compared with cluster analysis using a variety of distance and entropy metrics. The individual measurements are then evaluated based on where they fall within their clusters, and a laboratory-level scoring metric is developed, which provides an assessment of each laboratory's individual performance.

Interlaboratory Reproducibility of a Targeted Metabolomics Platform for Analysis of Human Serum and Plasma

A critical question facing the field of metabolomics is whether data obtained from different centers can be effectively compared and combined. An important aspect of this is the interlaboratory precision (reproducibility) of the analytical protocols used. We analyzed human samples in six laboratories using different instrumentation but a common protocol (the AbsoluteIDQ p180 kit) for the measurement of 189 metabolites via liquid chromatography (LC) or flow injection analysis (FIA) coupled to tandem mass spectrometry (MS/MS). In spiked quality control (QC) samples 82% of metabolite measurements had an interlaboratory precision of <20%, while 83% of averaged individual laboratory measurements were accurate to within 20%. For 20 typical biological samples (serum and plasma from healthy individuals) the median interlaboratory coefficient of variation (CV) was 7.6%, with 85% of metabolites exhibiting a median interlaboratory CV of <20%. Precision was largely independent of the type of sample (serum or plasma) or the anticoagulant used but was reduced in a sample from a patient with dyslipidaemia. The median interlaboratory accuracy and precision of the assay for standard reference plasma (NIST SRM 1950) were 107% and 6.7%, respectively. Likely sources of irreproducibility were the near limit of detection (LOD) typical abundance of some metabolites and the degree of manual review and optimization of peak integration in the LC-MS/MS data after acquisition. Normalization to a reference material was crucial for the semi-quantitative FIA measurements. This is the first interlaboratory assessment of a widely used, targeted metabolomics assay illustrating the reproducibility of the protocol and how data generated on different instruments could be directly integrated in large-scale epidemiological studies.

Complex mixtures by NMR and complex NMR for mixtures: experimental and publication challenges

Untargeted strategies have changed the rules of the game in complex mixture analysis, introducing an amazing potential for medical and biological applications that is just starting to be tapped. But with great power come great challenges; although untargeted mixture analysis opens the road for many exciting possibilities, the road is still full of perils. On the one hand, this article highlights some of the difficulties that need to be sorted for mixture analysis by NMR to fulfill its potential, along with insight on how they may be managed. Highlighted key points include the need for 'computer friendly' solutions for sharing data, experimental design and algorithm to facilitate the steady growth of knowledge and modeling ability in the field, and the need for large-scale studies to improve confidence in newly identified biomarkers. On the other hand, the second part of this article presents some breakthroughs in NMR experiments that, when combined, may modify the landscape of mixture analysis. Copyright © 2016 John Wiley & Sons, Ltd.

NMR window of molecular complexity showing homeostasis in superorganisms

NMR offers tremendous advantages in the analyses of molecular complexity. The “big-data” are produced during the acquisition of fingerprints that must be stored and shared for posterior analysis and verifications.

Contribution towards a Metabolite Profile of the Detoxification of Benzoic Acid through Glycine Conjugation: An Intervention Study

Benzoic acid is widely used as a preservative in food products and is detoxified in humans through glycine conjugation. Different viewpoints prevail on the physiological significance of the glycine conjugation reaction and concerns have been raised on potential public health consequences following uncontrolled benzoic acid ingestion. We performed a metabolomics study which used commercial benzoic acid containing flavored water as vehicle for designed interventions, and report here on the controlled consumption of the benzoic acid by 21 cases across 6 time points for a total of 126 time points. Metabolomics data from urinary samples analyzed by nuclear magnetic resonance spectroscopy were generated in a time-dependent cross-over study. We used ANOVA-simultaneous component analysis (ASCA), repeated measures analysis of variance (RM-ANOVA) and unfolded principal component analysis (unfolded PCA) to supplement conventional statistical methods to uncover fully the metabolic perturbations due to the xenobiotic intervention, encapsulated in the metabolomics tensor (three-dimensional matrices having cases, spectral areas and time as axes). Identification of the biologically important metabolites by the novel combination of statistical methods proved the power of this approach for metabolomics studies having complex data structures in general. The study disclosed a high degree of inter-individual variation in detoxification of the xenobiotic and revealed metabolic information, indicating that detoxification of benzoic acid through glycine conjugation to hippuric acid does not indicate glycine depletion, but is supplemented by ample glycine regeneration. The observations lend support to the view of maintenance of glycine homeostasis during detoxification. The study indicates also that time-dependent metabolomics investigations, using designed interventions, provide a way of interpreting the variation induced by the different factors of a designed experiment-an approach with potential to advance significantly our understanding of normal and pathophysiological perturbations of endogenous or exogenous origin.

Identification of a regulation network in response to cadmium toxicity using blood clam Tegillarca granosa as model

Clam, a filter-feeding lamellibranch mollusk, is capable to accumulate high levels of trace metals and has therefore become a model for investigation the mechanism of heavy metal toxification. In this study, the effects of cadmium were characterized in the gills of Tegillarca granosa during a 96-hour exposure course using integrated metabolomic and proteomic approaches. Neurotoxicity and disturbances in energy metabolism were implicated according to the metabolic responses after Cd exposure, and eventually affected the osmotic function of gill tissue. Proteomic analysis showed that oxidative stress, calcium-binding and sulfur-compound metabolism proteins were key factors responding to Cd challenge. A knowledge-based network regulation model was constructed with both metabolic and proteomic data. The model suggests that Cd stimulation mainly inhibits a core regulation network that is associated with histone function, ribosome processing and tight junctions, with the hub proteins actin, gamma 1 and Calmodulin 1. Moreover, myosin complex inhibition causes abnormal tight junctions and is linked to the irregular synthesis of amino acids. For the first time, this study provides insight into the proteomic and metabolomic changes caused by Cd in the blood clam T. granosa and suggests a potential toxicological pathway for Cd.

FoodPro: A Web-Based Tool for Evaluating Covariance and Correlation NMR Spectra Associated with Food Processes

Foods from agriculture and fishery products are processed using various technologies. Molecular mixture analysis during food processing has the potential to help us understand the molecular mechanisms involved, thus enabling better cooking of the analyzed foods. To date, there has been no web-based tool focusing on accumulating Nuclear Magnetic Resonance (NMR) spectra from various types of food processing. Therefore, we have developed a novel web-based tool, FoodPro, that includes a food NMR spectrum database and computes covariance and correlation spectra to tasting and hardness. As a result, FoodPro has accumulated 236 aqueous (extracted in D₂O) and 131 hydrophobic (extracted in CDCl₃) experimental bench-top 60-MHz NMR spectra, 1753 tastings scored by volunteers, and 139 hardness measurements recorded by a penetrometer, all placed into a core database. The database content was roughly classified into fish and vegetable groups from the viewpoint of different spectrum patterns. FoodPro can query a user food NMR spectrum, search similar NMR spectra with a specified similarity threshold, and then compute estimated tasting and hardness, covariance, and correlation spectra to tasting and hardness. Querying fish spectra exemplified specific covariance spectra to tasting and hardness, giving positive covariance for tasting at 1.31 ppm for lactate and 3.47 ppm for glucose and a positive covariance for hardness at 3.26 ppm for trimethylamine N-oxide.

Development of an in Situ NMR Photoreactor To Study Environmental Photochemistry

Photochemistry is a key environmental process directly linked to the fate, source, and toxicity of pollutants in the environment. This study explores two approaches for integrating light sources with nuclear magnetic resonance (NMR) spectroscopy: sample irradiation using a "sunlight simulator" outside the magnet versus direct irradiation of the sample inside the magnet. To assess their applicability, the in situ NMR photoreactors were applied to a series of environmental systems: an atmospheric pollutant (p-nitrophenol), crude oil extracts, and groundwater. The study successfully illustrates that environmentally relevant aqueous photochemical processes can be monitored in situ and in real time using NMR spectroscopy. A range of intermediates and degradation products were identified and matched to the literature. Preliminary measurements of half-lives were also obtained from kinetic curves. The sunlight simulator was shown to be the most suitable model to explore environmental photolytic processes in situ. Other light sources with more intense UV output hold potential for evaluating UV as a remediation alternative in areas such as wastewater treatment plants or oil spills. Finally, the ability to analyze the photolytic fate of trace chemicals at natural abundance in groundwater, using a cryogenic probe, demonstrates the viability of NMR spectroscopy as a powerful and complementary technique for environmental applications in general.

Metabolomics in rheumatic diseases: desperately seeking biomarkers

Metabolomics enables the profiling of large numbers of small molecules in cells, tissues and biological fluids. These molecules, which include amino acids, carbohydrates, lipids, nucleotides and their metabolites, can be detected quantitatively. Metabolomic methods, often focused on the information-rich analytical techniques of NMR spectroscopy and mass spectrometry, have potential for early diagnosis, monitoring therapy and defining disease pathogenesis in many therapeutic areas, including rheumatic diseases. By performing global metabolite profiling, also known as untargeted metabolomics, new discoveries linking cellular pathways to biological mechanisms are being revealed and are shaping our understanding of cell biology, physiology and medicine. These pathways can potentially be targeted to diagnose and treat patients with immune-mediated diseases.

The interactive effects of mercury and selenium on metabolic profiles, gene expression and antioxidant enzymes in halophyte Suaeda salsa

Suaeda salsa is the pioneer halophyte in the Yellow River Delta and was consumed as a popular vegetable. Mercury has become a highly risky contaminant in the sediment of intertidal zones of the Yellow River Delta. In this work, we investigated the interactive effects of mercury and selenium in S. salsa on the basis of metabolic profiling, antioxidant enzyme activities and gene expression quantification. Our results showed that mercury exposure (20 μg L(-1)) inhibited plant growth of S. salsa and induced significant metabolic responses and altered expression levels of INPS, CMO, and MDH in S. salsa samples, together with the increased activities of antioxidant enzymes including SOD and POD. Overall, these results indicated osmotic and oxidative stresses, disturbed protein degradation and energy metabolism change in S. salsa after mercury exposures. Additionally, the addition of selenium could induce both antagonistic and synergistic effects including alleviating protein degradation and aggravating osmotic stress caused by mercury.

Metabolomics reveals energetic impairments in Daphnia magna exposed to diazinon, malathion and bisphenol-A

(1)H nuclear magnetic resonance (NMR)-based metabolomics was used to study the response of Daphnia magna to increasing sub-lethal concentrations of either an organophosphate (diazinon or malathion) or bisphenol-A (BPA). Principal component analysis (PCA) of (1)H NMR spectra were used to screen metabolome changes after 48h of contaminant exposure. The PCA scores plots showed that diazinon exposures resulted in aberrant metabolomic profiles at all exposure concentrations tested (0.009-0.135 μg/L), while for malathion the second lowest (0.08μg/L) and two highest exposure concentrations (0.32μg/L and 0.47μg/L) caused significant shifts from the control. Individual metabolite changes for both organophosphates indicated that the response to increasing exposure was non-linear and described perturbations in the metabolome that were characteristic of the severity of exposure. For example, intermediate concentrations of diazinon (0.045μg/L and 0.09μg/L) and malathion (0.08μg/L) elicited a decrease in amino acids such as leucine, valine, arginine, glycine, lysine, glutamate, glutamine, phenylalanine and tyrosine, with concurrent increases in glucose and lactate, suggesting a mobilization of energy resources to combat stress. At the highest exposure concentrations for both organophosphates there was evidence of a cessation in metabolic activity, where the same amino acids increased and glucose and lactate decreased, suggesting a slowdown in protein synthesis and depletion of energy stocks. This demonstrated a similar response in the metabolome between two organophosphates but also that intermediate and severe stress levels could be differentiated by changes in the metabolome. For BPA exposures, the PCA scores plot showed a significant change in metabolome at 0.1mg/L, 1.4mg/L and 2.1mg/L of exposure. Individual metabolite changes from 0.7 to 2.1mg/L of BPA exposure showed increases in amino acids such as alanine, valine, isoleucine, leucine, arginine, phenylalanine and tyrosine. These metabolite changes were correlated with decreases in glucose and lactate. This pattern of response was also seen in the highest organophosphate exposures and suggested a generalized stress response that could be related to altered energy dynamics in D. magna. Through studying increasing exposure responses, we have demonstrated the ability of metabolomics to identify discrete differences between intermediate and severe stress, and also to characterize how systemic stress is manifested in the metabolome.

Probing Cancer Cell Metabolism Using NMR Spectroscopy

Altered cellular metabolism is now accepted to be at the core of many diseases including cancer. Over the past 20 years, NMR has become a core technology to study these metabolic perturbations in detail. This chapter reviews current NMR-based methods for steady-state metabolism and, in particular, the use of non-radioactive stable isotope-enriched tracers. Opportunities and challenges for each method, such as 1D (1)H NMR spectroscopy and (13)C carbon-based NMR spectroscopic methods, are discussed. Ultimately, the combination of NMR and mass spectra as orthogonal technologies are required to compensate for the drawbacks of each technique when used singly are discussed.

(1)H-NMR screening for the high-throughput determination of genotype and environmental effects on the content of asparagine in wheat grain

Free asparagine in cereals is known to be the precursor of acrylamide, a neurotoxic and carcinogenic product formed during cooking processes. Thus, the development of crops with lower asparagine is of considerable interest to growers and the food industry. In this study, we describe the development and application of a rapid (1)H-NMR-based analysis of cereal flour, that is, suitable for quantifying asparagine levels, and hence acrylamide-forming potential, across large numbers of samples. The screen was applied to flour samples from 150 bread wheats grown at a single site in 2005, providing the largest sample set to date. Additionally, screening of 26 selected cultivars grown for two further years in the same location and in three additional European locations in the third year (2007) provided six widely different environments to allow estimation of the environmental (E) and G x E effects on asparagine levels. Asparagine concentrations in the 150 genotypes ranged from 0.32 to 1.56 mg/g dry matter in wholemeal wheat flours. Asparagine levels were correlated with plant height and therefore, due to recent breeding activities to produce semi-dwarf varieties, a negative relationship with the year of registration of the cultivar was also observed. The multisite study indicated that only 13% of the observed variation in asparagine levels was heritable, whilst the environmental contribution was 36% and the GxE component was 43%. Thus, compared to some other phenotypic traits, breeding for low asparagine wheats presents a difficult challenge.

Effects of heat-treatment on the stability and composition of metabolomic extracts from the earthworm Eisenia fetida

Environmental metabolomics studies employing earthworms as sentinels for soil contamination are numerous, but the instability of the metabolite extracts from these organisms has been minimally addressed. This study evaluated the efficacy of adding a heat-treatment step in two commonly used extraction protocols (Bligh and Dyer and D₂O phosphate buffer) as a pre-analytical stabilization method. The resulting metabolic profiles of Eisenia fetida were assessed using principal component analysis and NMR spectral evaluations. The heated Bligh and Dyer extractions produced stabilized profiles with minimal variation of the extracted metabolomic profiles over time, providing a more suitable method for metabolomic analysis of earthworm extracts.