Expanding the limits of human blood metabolite quantitation using NMR spectroscopy

Metabolite assignment of ultrafiltered synovial fluid extracted from knee joints of reactive arthritis patients using high resolution NMR spectroscopy

Currently, there are no reliable biomarkers available that can aid early differential diagnosis of reactive arthritis (ReA) from other inflammatory joint diseases. Metabolic profiling of synovial fluid (SF)-obtained from joints affected in ReA-holds great promise in this regard and will further aid monitoring treatment and improving our understanding about disease mechanism. As a first step in this direction, we report here the metabolite specific assignment of ¹ H and ¹³ C resonances detected in the NMR spectra of SF samples extracted from human patients with established ReA. The metabolite characterization has been carried out on both normal and ultrafiltered (deproteinized) SF samples of eight ReA patients (n = 8) using high-resolution (800 MHz) ¹ H and ¹ H─¹³ C NMR spectroscopy methods such as one-dimensional ¹ H CPMG and two-dimensional J-resolved¹ H NMR and homonuclear ¹ H─¹ H TOCSY and heteronuclear¹ H─¹³ C HSQC correlation spectra. Compared with normal SF samples, several distinctive ¹ H NMR signals were identified and assigned to metabolites in the ¹ H NMR spectra of ultrafiltered SF samples. Overall, we assigned 53 metabolites in normal filtered SF and 64 metabolites in filtered pooled SF sample compared with nonfiltered SF samples for which only 48 metabolites (including lipid/membrane metabolites as well) have been identified. The established NMR characterization of SF metabolites will serve to guide future metabolomics studies aiming to identify/evaluate the SF-based metabolic biomarkers of diagnostic/prognostic potential or seeking biochemical insights into disease mechanisms in a clinical perspective.

Analysis of Plasma, Serum, and Whole Blood Metabolites Using 1H NMR Spectroscopy

Blood is the most widely used biological specimen in the metabolomics field. With its unique characteristics of high reproducibility and excellent quantitation, NMR spectroscopy offers immense benefits for the analysis of blood metabolites. In the metabolomics field, intact blood serum and plasma have been widely used for many years. However, such analysis has met with challenges arising from the deleterious effects of the abundant proteins in serum and plasma. Recent advances have led to the development of improved NMR methods that involve removal of protein before analysis. In particular, protein removal by precipitation using methanol alone or using a mixture of methanol and chloroform was shown to be an optimal method for metabolite recovery and for producing highly resolved NMR spectra. This has led to the absolute quantitation of nearly 70 metabolites in serum and plasma and nearly 80 in whole blood. In this chapter, we describe protocols for the analysis of blood serum, blood plasma, and whole blood metabolites using 1D ¹H NMR spectroscopy methods.

Analysis of Coenzymes and Antioxidants in Tissue and Blood Using 1D 1H NMR Spectroscopy

Cellular coenzymes including coenzyme A (CoA), acetyl coenzyme A (acetyl-CoA), coenzymes of redox reactions and of energy, and antioxidants mediate biochemical reactions fundamental to the functioning of all living cells. The redox coenzymes include NAD⁺ (oxidized nicotinamide adenine dinucleotide), NADH (reduced nicotinamide adenine dinucleotide), NADP⁺ (oxidized nicotinamide adenine dinucleotide phosphate), and NADPH (reduced nicotinamide adenine dinucleotide phosphate); the energy coenzymes include ATP (adenosine triphosphate), ADP (adenosine diphosphate), and AMP (adenosine monophosphate); and the antioxidants include GSSG (oxidized glutathione) and GSH (reduced glutathione). Their measurement is important to better understand cellular metabolism. Recent advances have pushed the limit of metabolite quantitation using NMR methods to an unprecedented level, which offer a new avenue for analysis of the coenzymes and antioxidants. Unlike the conventional enzyme assays, which need separate protocols for analysis, a simple 1D ¹H NMR experiment enables analysis of all these molecular species in one step. In this chapter, we describe protocols for their identification and quantitation in tissue and whole blood using NMR spectroscopy.

A novel method of sample homogenization with the use of a microtome-cryostat apparatus

Quantitative metabolomics places high demands on sample preparation, including a high degree of metabolite extraction and controlled sample weight. In respect to elastic collagen-rich tissues, the existing methods of sample homogenization poorly fit these demands due to incomplete homogenization, sample material loss, or metabolite degradation. Herein, a novel method based on the use of a microtome-cryostat apparatus is proposed. The performance of the cryotome method is compared with the results obtained with the use of a vortex bead beating. NMR-based metabolomic analysis shows that the extraction efficiency and the data scattering for both methods of sample preparation are similar. However, the heat generation during the bead beating causes the destruction of thermally-unstable compounds; besides, it may cause protein hydrolysis, leading to an artificial increase in the amino acid level. The cryotome method of sample homogenization does not cause sample heating, and it seems to be ideal for elastic tissues.

A novel method of homogenization of elastic tissues does not cause sample heating and material losses.

Overview of NMR Spectroscopy-Based Metabolomics: Opportunities and Challenges

The fast-growing field of metabolomics is impacting numerous areas of basic and life sciences. In metabolomics, analytical methods play a pivotal role, and nuclear magnetic resonance (NMR) and mass spectrometry (MS) have proven to be the most suitable and powerful methods. Although NMR exhibits lower sensitivity and resolution compared to MS, NMR's numerous important characteristics far outweigh its limitations. Some of its characteristics include excellent reproducibility and quantitative accuracy, the capability to analyze intact biospecimens, an unparalleled ability to identify unknown metabolites, the ability to trace in-cell and in-organelle metabolism in real time, and the capacity to trace metabolic pathways atom by atom using ²H, ¹³C, or ¹⁵N isotopes. Each of these characteristics has been exploited extensively in numerous studies. In parallel, the field has witnessed significant progress in instrumentation, methods development, databases, and automation that are focused on higher throughput and alleviating the limitations of NMR, in particular, resolution and sensitivity. Despite the advances, however, the high complexity of biological mixtures combined with the limitations in sensitivity and resolution continues to pose major challenges. These challenges need to be dealt with effectively to better realize the potential of metabolomics, in general. As a result, multifaceted efforts continue to focus on addressing the challenges as well as reaping the benefits of NMR-based metabolomics. This chapter highlights the current status with emphasis on the opportunities and challenges in NMR-based metabolomics.

Rapid, Reproducible, Quantifiable NMR Metabolomics: Methanol and Methanol: Chloroform Precipitation for Removal of Macromolecules in Serum and Whole Blood

Background: Though blood is an excellent biofluid for metabolomics, proteins and lipids present in blood can interfere with 1d-¹H NMR spectra and disrupt quantification of metabolites. Here, we present effective macromolecule removal strategies for serum and whole blood (WB) samples. Methods: A variety of macromolecule removal strategies were compared in both WB and serum, along with tests of ultrafiltration alone and in combination with precipitation methods. Results: In healthy human serum, methanol:chloroform:water extraction with ultrafiltration was compared to methanol precipitation with and without ultrafiltration. Methods were tested in healthy pooled human serum, and in serum from patients with sepsis. Effects of long-term storage at −80 °C were tested to explore the impact of macromolecule removal strategy on serum from different conditions. In WB a variety of extraction strategies were tested in two types of WB (from pigs and baboons) to examine the impact of macromolecule removal strategies on different samples. Conclusions: In healthy human serum methanol precipitation of serum with ultrafiltration was superior, but was similar in recovery and variance to methanol:chloroform:water extraction with ultrafiltration in pooled serum from patients with sepsis. In WB, high quality, quantifiable spectra were obtained with the use of a methanol: chloroform precipitation.

Metabolomic signature of the postprandial experience

BACKGROUND

Ingestion of a meal up to maximal tolerance induces unpleasant fullness sensation and changes in circulating metabolites. Our aim was to evaluate the relation between postprandial sensations and the metabolomic responses to a comfort meal.

METHODS

In 32 non-obese healthy men, homeostatic sensations (hunger/satiety, fullness), hedonic sensations (digestive well-being, mood), and the metabolomic profile in plasma (low-molecular weight metabolites and lipoprotein profiles) were measured before and 20 minutes after a comfort meal (warm ham and cheese sandwich and juice; total 300 mL; 425 kcal). Perception was measured on 10 cm scales and the metabolomic response by nuclear magnetic resonance spectroscopy.

KEY RESULTS

The comfort meal induced homeostatic sensations (satiety and fullness) associated with a positive hedonic reward (enhanced digestive well-being and mood) and a clear change in the metabolomic profile with a sharp discrimination between the pre and postprandial state by a non-supervised principal component analysis. The change in circulating metabolites correlated with the postprandial sensations: the increase in alanine correlated with the increase in fullness (R = 0.50; P = 0.004) and well-being (R = 0.50; P = 0.004); the increase in glucose correlated with the sensation of fullness (R = 0.40; P = 0.023) and enhanced mood (R = 0.41; P = 0.020).

CONCLUSION AND INFERENCES

Metabolomic changes in the response to a meal may provide an objective index of the postprandial experience, which may have clinical implications in the management of patients with poor meal tolerance or meal-related symptoms.

Evaluation of sample preparation methods for NMR-based metabolomics of cow milk

The quality of milk metabolome analyzed by nuclear magnetic resonance (NMR) is greatly influenced by the way samples are prepared. Although this analytical method is increasingly used to study milk metabolites, a thorough examination of available sample preparation protocols for milk has not been reported yet. We evaluated the performance of eight milk preparation methods namely (1) raw milk without any processing; (2) skimmed milk; (3) ultrafiltered milk; (4) skimming followed by ultrafiltration; (5) ultracentrifuged milk; (6) methanol; (7) dichloromethane; and (8) methanol/dichloromethane, in terms of spectra quality, repeatability, signal-to-noise ratio, extraction efficiency and yield criteria. A pooled sample of milk was used for all protocols. Skimming, ultracentrifugation and unprocessed milk protocols showed poor NMR spectra quality. Protocols involving multiple steps, namely methanol/dichloromethane extraction, and skimming followed by ultrafiltration produced inadequate results for signal-to-noise ratio parameter. Methanol and skimming associated to ultrafiltration provided good repeatability results compared to the other protocols. Chemical-based sample preparation protocols, particularly methanol, showed more efficient metabolite extraction compared to physical preparation methods. When considering all evaluation parameters, the methanol extraction protocol proved to be the best method. As a proof of utility, methanol protocol was then applied to milk samples from dairy cows fed a diet with or without a feed additive, showing a clear separation between the two groups of cows.

NMR spectroscopy enables simultaneous quantification of carbohydrates for diagnosis of intestinal and gastric permeability

Increased intestinal or gastric permeability is one of the major hallmarks of liver cirrhosis. The current gold standard for diagnosis of aberrant gut permeability due to disease is the triple-sugar test, where carbohydrates are orally administered and urinary excretion is measured. Hereby, elevated lactulose levels indicate intestinal permeability, whereas increased sucrose levels reveal gastric permeability. However, reliable detection and quantification of these sugars in a complex biological fluid still remains challenging due to interfering substances. Here we used Nuclear Magnetic Resonance (NMR) spectroscopy with a simple and fast protocol, without any additional sample extraction steps, for straight-forward simultaneous quantification of sugars in urine in order to detect increased intestinal and gastric permeability. Collected urine samples were diluted in buffer and one- and two-dimensional proton spectra were recorded in order to reveal carbohydrate concentrations in individual urine samples containing mannitol, sucrose and/or lactulose. Overall, this article presents a fast and robust method for simultaneous quantification of different sugars down to low micro-molar concentrations for research studies and can be further extended for clinical studies with automation of the quantification process.

Metabolic profiling and targeted lipidomics reveals a disturbed lipid profile in mothers and fetuses with intrauterine growth restriction

Fetal growth may be impaired by poor placental function or maternal conditions, each of which can influence the transfer of nutrients and oxygen from the mother to the developing fetus. Large-scale studies of metabolites (metabolomics) are key to understand cellular metabolism and pathophysiology of human conditions. Herein, maternal and cord blood plasma samples were used for NMR-based metabolic fingerprinting and profiling, including analysis of the enrichment of circulating lipid classes and subclasses, as well as the number of sub-fraction particles and their size. Changes in phosphatidylcholines and glycoproteins were prominent in growth-restricted fetuses indicating significant alterations in their abundance and biophysical properties. Lipoprotein profiles showed significantly lower plasma concentrations of cholesterol-intermediate density lipoprotein (IDL), triglycerides-IDL and high-density lipoprotein (HDL) in mothers of growth-restricted fetuses compared to controls (p < 0.05). In contrast, growth-restricted fetuses had significantly higher plasma concentrations of cholesterol and triglycerides transporting lipoproteins [LDL, IDL, and VLDL, (p < 0.005; all)], as well as increased VLDL particle types (large, medium and small). Significant changes in plasma concentrations of formate, histidine, isoleucine and citrate in growth-restricted fetuses were also observed. Comprehensive metabolic profiling reveals that both, mother and fetuses of pregnancies complicated with fetal growth restriction have a substantial disruption in lipid metabolism.

Metabolic fingerprint of insulin resistance in human polymorphonuclear leucocytes

The present study was aimed at determining the metabolic profile of PMNs in obese subjects, and to explore its potential relationship with insulin resistance (IR). To achieve this goal, a pilot clinical study was performed using PMNs from 17 patients with obesity and IR, and 17 lean controls without IR, which was validated in an additional smaller cohort (consisting of 10 patients and 10 controls). PMNs were isolated from peripheral blood and nuclear magnetic resonance was used to perform the metabolomic analysis. A total of 48 metabolites were quantified. The main metabolic change found in PMNs was a significant increase in 2-aminoisobutyric acid with a direct correlation with HOMA-IR (p<0.001), BMI (p<0.000001) and waist circumference (p<0.000001). By contrast, a decrease of 3-hydroxyisovalerate was observed with an inverse correlation with HOMA-IR (p = 0.001), BMI (p = 0.001) and waist circumference (p = 0.0001). Notably, the metabolic profile in plasma was different than that obtained in PMNs. In summary, our results suggest that the change in 3-hydroxyisovalerate and 2-aminoisobutyric is the key metabolic fingerprint in PMNs of obese subjects with IR. In addition, our methodology could be an easy and reliable tool for monitoring the effect of treatments in the setting of precision medicine.

Elevated circulating levels of succinate in human obesity are linked to specific gut microbiota

Gut microbiota-related metabolites are potential clinical biomarkers for cardiovascular disease (CVD). Circulating succinate, a metabolite produced by both microbiota and the host, is increased in hypertension, ischemic heart disease, and type 2 diabetes. We aimed to analyze systemic levels of succinate in obesity, a major risk factor for CVD, and its relationship with gut microbiome. We explored the association of circulating succinate with specific metagenomic signatures in cross-sectional and prospective cohorts of Caucasian Spanish subjects. Obesity was associated with elevated levels of circulating succinate concomitant with impaired glucose metabolism. This increase was associated with specific changes in gut microbiota related to succinate metabolism: a higher relative abundance of succinate-producing Prevotellaceae (P) and Veillonellaceae (V), and a lower relative abundance of succinate-consuming Odoribacteraceae (O) and Clostridaceae (C) in obese individuals, with the (P + V/O + C) ratio being a main determinant of plasma succinate. Weight loss intervention decreased (P + V/O + C) ratio coincident with the reduction in circulating succinate. In the spontaneous evolution after good dietary advice, alterations in circulating succinate levels were linked to specific metagenomic signatures associated with carbohydrate metabolism and energy production with independence of body weight change. Our data support the importance of microbe-microbe interactions for the metabolite signature of gut microbiome and uncover succinate as a potential microbiota-derived metabolite related to CVD risk.

A Metabolomics Study of BPTES Altered Metabolism in Human Breast Cancer Cell Lines

The Warburg effect is a well-known phenomenon in cancer, but the glutamine addiction in which cancer cells utilize glutamine as an alternative source of energy is less well known. Recent efforts have focused on preventing cancer cell proliferation associated with glutamine addiction by targeting glutaminase using the inhibitor BPTES (bis-2-(5-phenylacetamido-1,3,4-thiadiazol-2-yl)ethyl sulfide). In the current study, an investigation of the BPTES induced changes in metabolism was made in two human breast cancer cell lines, MCF7 (an estrogen receptor dependent cell line) and MDA-MB231 (a triple negative cell line), relative to the non-cancerous cell line, MCF10A. NMR spectroscopy combined with a recently established smart-isotope tagging approach enabled quantitative analysis of 41 unique metabolites representing numerous metabolite classes including carbohydrates, amino acids, carboxylic acids and nucleotides. BPTES induced metabolism changes in the cancer cell lines were especially pronounced under hypoxic conditions with up to 1/3 of the metabolites altered significantly (p < 0.05) relative to untreated cells. The BPTES induced changes were more pronounced for MCF7 cells, with 14 metabolites altered significantly (p < 0.05) compared to seven for MDA-MB231. Analyses of the results indicate that BPTES affected numerous metabolic pathways including glycolysis, TCA cycle, nucleotide and amino acid metabolism in cancer. The distinct metabolic responses to BPTES treatment determined in the two breast cancer cell lines offer valuable metabolic information for the exploration of the therapeutic responses to breast cancer.

Profiling Redox and Energy Coenzymes in Whole Blood, Tissue and Cells Using NMR Spectroscopy

Coenzymes of cellular redox reactions and cellular energy, as well as antioxidants mediate biochemical reactions fundamental to the functioning of all living cells. Conventional analysis methods lack the opportunity to evaluate these important redox and energy coenzymes and antioxidants in a single step. Major coenzymes include redox coenzymes: NAD⁺ (oxidized nicotinamide adenine dinucleotide), NADH (reduced nicotinamide adenine dinucleotide), NADP⁺ (oxidized nicotinamide adenine dinucleotide phosphate) and NADPH (reduced nicotinamide adenine dinucleotide phosphate); energy coenzymes: ATP (adenosine triphosphate), ADP (adenosine diphosphate) and AMP (adenosine monophosphate); and antioxidants: GSSG (oxidized glutathione) and GSH (reduced glutathione). We show here that a simple ¹H NMR experiment can measure these coenzymes and antioxidants in tissue and whole blood apart from a vast pool of other metabolites. In addition, focused on the goal of identification of coenzymes in subcellular fractions, we demonstrate analysis of coenzymes in the cytoplasm using breast cancer cells. Owing to their unstable nature, or low concentrations, most of the coenzymes either evade detection or lose their integrity when established sample preparation and analysis methods are used. To overcome this challenge, here we describe the development of new methods to detect these molecules without affecting the integrity of other metabolites. We used an array of 1D and 2D NMR methods, chemical shift databases, pH measurements and spiking with authentic compounds to establish the identity of peaks for the coenzymes and antioxidants in NMR spectra. Interestingly, while none of the coenzymes and antioxidants were detected in plasma, they were abundant in whole blood. Considering that the coenzymes and antioxidants represent a sensitive measure of human health and risk for numerous diseases, the presented NMR methods to measure them in one step potentially open new opportunities in the metabolomics field.

Beyond the limit of assignment of metabolites using minimal serum samples and 1H NMR spectroscopy with cross-validation by mass spectrometry

Identification of NMR-based metabolic indexes is limited by the deleterious effects of copious proteins and lipoproteins in the serum that accentuate the need for advance and high-throughput method. We tried to explore the use of a novel filtration (2KDa molecular weight cut-off) approach to remove the proteins from serum following use of less sample volume (only 150 μL of filtered serum), combining an array of 1D/2D NMR experiments (at 800 MHz spectrometer), spiking experiments with standard compounds, and validated by mass spectrometry. This novel method enabled the identification of a large number (n = 73) of metabolites and their percentage of abundance in the present study cohort. Mass spectrometry further validates and confirms the presence of all these 73 metabolites using same filtered serum. This study reveals seven new metabolites (citrulline, inosine, taurine, trimethyl amine, methylmalonate, uracil, methanol) in filtered serum using 1D/2D NMR spectroscopy that were not observed in earlier available literature using protein precipitation approach. This novel method delineates volatile metabolites, nitrogenous bases and nucleosides that may provide a milestone for the identification of inborn error of metabolism, pathogenicity at molecular level, disease identification and prognosis, and forensic studies using minimal volume of filtered serum samples and NMR spectroscopy.

AQuA: An Automated Quantification Algorithm for High-Throughput NMR-Based Metabolomics and Its Application in Human Plasma

A key limiting step for high-throughput NMR-based metabolomics is the lack of rapid and accurate tools for absolute quantification of many metabolites. We developed, implemented, and evaluated an algorithm, AQuA (Automated Quantification Algorithm), for targeted metabolite quantification from complex ¹H NMR spectra. AQuA operates based on spectral data extracted from a library consisting of one standard calibration spectrum for each metabolite. It uses one preselected NMR signal per metabolite for determining absolute concentrations and does so by effectively accounting for interferences caused by other metabolites. AQuA was implemented and evaluated using experimental NMR spectra from human plasma. The accuracy of AQuA was tested and confirmed in comparison with a manual spectral fitting approach using the ChenomX software, in which 61 out of 67 metabolites quantified in 30 human plasma spectra showed a goodness-of-fit (r²) close to or exceeding 0.9 between the two approaches. In addition, three quality indicators generated by AQuA, namely, occurrence, interference, and positional deviation, were studied. These quality indicators permit evaluation of the results each time the algorithm is operated. The efficiency was tested and confirmed by implementing AQuA for quantification of 67 metabolites in a large data set comprising 1342 experimental spectra from human plasma, in which the whole computation took less than 1 s.

NMR-Guided Mass Spectrometry for Absolute Quantitation of Human Blood Metabolites

Broad-based, targeted metabolite profiling using mass spectrometry (MS) has become a major platform used in the field of metabolomics for a variety of applications. However, quantitative MS analysis is challenging owing to numerous factors including (1) the need for, ideally, isotope-labeled internal standards for each metabolite, (2) the fact that such standards may be unavailable or prohibitively costly, (3) the need to maintain the standards' concentrations close to those of the target metabolites, and (4) the alternative use of time-consuming calibration curves for each target metabolite. Here, we introduce a new method in which metabolites from a single serum specimen are quantified on the basis of a recently developed NMR method [ Nagana Gowda et al. Anal. Chem. 2015 , 87 , 706 ] and then used as references for absolute metabolite quantitation using MS. The MS concentrations of 30 metabolites thus derived for test serum samples exhibited excellent correlations with the NMR ones (R² > 0.99) with a median CV of 3.2%. This NMR-guided-MS quantitation approach is simple and easy to implement and offers new avenues for the routine quantification of blood metabolites using MS. The demonstration that NMR and MS data can be compared and correlated when using identical sample preparations allows improved opportunities to exploit their combined strengths for biomarker discovery and unknown-metabolite identification. Intriguingly, however, metabolites including glutamine, pyroglutamic acid, glucose, and sarcosine correlated poorly with NMR data because of stability issues in their MS analyses or weak or overlapping signals. Such information is potentially important for improving biomarker discovery and biological interpretations. Further, the new quantitation method demonstrated here for human blood serum can in principle be extended to a variety of biological mixtures.

Exploring the biomarkers and therapeutic mechanism of kidney-yang deficiency syndrome treated by You-gui pill using systems pharmacology and serum metabonomics

In this study, systems pharmacology was used to predict the molecular targets of You-gui pill (YGP) and explore the therapeutic mechanism of Kidney-Yang Deficiency Syndrome (KYDS) treated with YGP. On the basis of this, serum samples from control group, KYDS model group and YGP group rats were studied using 1H NMR to verify the results of systems pharmacology from the level of metabonomics. Simultaneously, 1H NMR spectra of serum samples were obtained and statistically assessed using pattern recognition analysis. Biochemical analyses of serums were performed via radioimmunoassays. Furthermore, histopathological studies were conducted on the pituitary, adrenal, and thyroid glands, and testicles of the control, KYDS and YGP rats. Using systems pharmacology to analyze the active components of YGP, 61 active compounds were finally found. These compounds were likely to have an effect on 3177 target proteins and involve 234 pathways. Using metabonomics to analyze serum from KYDS rats treated with YGP, 22 endogenous biomarkers were found. These biomarkers were mainly involved in 10 metabolic pathways. Combining systems pharmacology and metabonomics, we found that the regulation of KYDS was primarily associated with 19 active compounds of 5 Chinese herbal medicines in YGP. These active compounds mainly had an effect on 8 target proteins, including phosphoenolpyruvate carboxykinase, betaine-homocysteine s-methyltransferase 1, alcohol dehydrogenase 1C, etc. These target proteins were primarily involved in 6 overlapping pathways, namely aminoacyl-tRNA biosynthesis, glycolysis/gluconeogenesis, glycine, serine and threonine metabolism, valine, leucine and isoleucine biosynthesis, arginine and proline metabolism, and pyruvate metabolism. In addition, there were 4 non-overlapping pathways, respectively alanine, aspartate and glutamate metabolism, d-glutamine and d-glutamate metabolism, ubiquinone and other terpenoid-quinone biosynthesis, and galactose metabolism. In summary, the therapeutic effects of YGP on KYDS were mainly associated with neuroendocrine regulation, energy metabolism, amino acid metabolism, inflammatory responses, apoptosis, oxidative stress and intestinal flora metabolism. What's more, we also found that YGP possessed the potential to protect liver and kidney function. Our study demonstrated that systems pharmacology and metabonomics methods were novel strategies for the exploration of the mechanisms of KYDS and TCM formulas.

Metabolic effects of Hedyotis diffusa on rats bearing Walker 256 tumor revealed by NMR-based metabolomics

Hedyotis diffusa, a traditional Chinese herbal medicine, is widely used for oncotherapy and shows a positive effect in the clinical treatment. But its mechanism of anticancer activities is complicated and unclear. This study was undertaken to assess the therapeutic effects and reveal detailed mechanisms of H. diffusa for oncotherapy. A Walker 256 tumor-bearing rat model was established, and metabolomic profiles of plasma and urine were obtained from ¹ H NMR technique. Multivariate statistical analysis methods were used to characterize the discriminating metabolites between control (C), Walker 256 tumor-bearing rats model (M), and H. diffusa treatment (H) groups. Finally, 13 and 10 metabolomic biomarkers in urine and plasma samples were further identified as characteristic metabolites in M group, whereas H group showed a partial metabolic balance recovered, such as ornithine, N-acetyl-l-aspartate, l-aspartate, and creatinine in urine samples, and acetate, lactate, choline, l-glutamine, and 3-hydroxybutyrate in plasma samples. On the basis of the methods above, we hypothesized H. diffusa treatment reduced the injury caused by Walker 256 tumor and maintained a metabolic balance. Our study demonstrated that this method provided new insights into metabolic alterations in tumor-bearing biosystems and researching on the effects of H. diffusa on the endogenous metabolism in tumor-bearing rats.

Spin System Modeling of Nuclear Magnetic Resonance Spectra for Applications in Metabolomics and Small Molecule Screening

The exceptionally rich information content of nuclear magnetic resonance (NMR) spectra is routinely used to identify and characterize molecules and molecular interactions in a wide range of applications, including clinical biomarker discovery, drug discovery, environmental chemistry, and metabolomics. The set of peak positions and intensities from a reference NMR spectrum generally serves as the identifying signature for a compound. Reference spectra normally are collected under specific conditions of pH, temperature, and magnetic field strength, because changes in conditions can distort the identifying signatures of compounds. A spin system matrix that parametrizes chemical shifts and coupling constants among spins provides a much richer feature set for a compound than a spectral signature based on peak positions and intensities. Spin system matrices expand the applicability of NMR spectral libraries beyond the specific conditions under which data were collected. In addition to being able to simulate spectra at any field strength, spin parameters can be adjusted to systematically explore alterations in chemical shift patterns due to variations in other experimental conditions, such as compound concentration, pH, or temperature. We present methodology and software for efficient interactive optimization of spin parameters against experimental 1D-¹H NMR spectra of small molecules. We have used the software to generate spin system matrices for a set of key mammalian metabolites and are also using the software to parametrize spectra of small molecules used in NMR-based ligand screening. The software, along with optimized spin system matrix data for a growing number of compounds, is available from http://gissmo.nmrfam.wisc.edu/ .

An NMR-Based Metabolomic Approach to Unravel the Preventive Effect of Water-Soluble Extract from Dendrobium officinale Kimura & Migo on Streptozotocin-Induced Diabetes in Mice

Dendrobium officinale Kimura & Migo (D. officinale) is a precious herbal medicine. In this study, we investigated metabolic mechanism underlying the effect of D. officinale water extract (DOWE) on diabetes prevention in mice after streptozotocin (STZ) exposure using NMR-based metabolomics. Interestingly, we found a decrease in blood glucose and an increase in liver glycogen in mice pretreated with DOWE after STZ exposure. The DOWE pretreatment significantly increased citrate and glutamine in the serum as well as creatine, alanine, leucine, isoleucine, valine, glutamine, glutathione and taurine in the liver of STZ-treated mice. Furthermore, serum glucose was significantly negatively correlated with citrate, pyruvate, alanine, isoleucine, histidine and glutamine in the serum as well as alanine and taurine in the liver. These findings suggest that the effect of DOWE on diabetes prevention may be linked to increases in liver glycogen and taurine as well as the up-regulation of energy and amino acid metabolism.

Alternatives to Nuclear Overhauser Enhancement Spectroscopy Presat and Carr-Purcell-Meiboom-Gill Presat for NMR-Based Metabolomics

NMR metabolomics are primarily conducted with 1D nuclear Overhauser enhancement spectroscopy (NOESY) presat for water suppression and Carr-Purcell-Meiboom-Gill (CPMG) presat as a T2 filter to remove macromolecule signals. Others pulse sequences exist for these two objectives but are not often used in metabolomics studies, because they are less robust or unknown to the NMR metabolomics community. However, recent improvements on alternative pulse sequences provide attractive alternatives to 1D NOESY presat and CPMG presat. We focus this perspective on PURGE, a water suppression technique, and PROJECT presat, a T2 filter. These two pulse sequences, when optimized, performed at least on par with 1D NOESY presat and CPMG presat, if not better. These pulse sequences were tested on common samples for metabolomics, human plasma, and urine.

Toward Reliable Lipoprotein Particle Predictions from NMR Spectra of Human Blood: An Interlaboratory Ring Test

Lipoprotein profiling of human blood by ¹H nuclear magnetic resonance (NMR) spectroscopy is a rapid and promising approach to monitor health and disease states in medicine and nutrition. However, lack of standardization of measurement protocols has prevented the use of NMR-based lipoprotein profiling in metastudies. In this study, a standardized NMR measurement protocol was applied in a ring test performed across three different laboratories in Europe on plasma and serum samples from 28 individuals. Data was evaluated in terms of (i) spectral differences, (ii) differences in LPD predictions obtained using an existing prediction model, and (iii) agreement of predictions with cholesterol concentrations in high- and low-density lipoproteins (HDL and LDL) particles measured by standardized clinical assays. ANOVA-simultaneous component analysis (ASCA) of the ring test spectral ensemble that contains methylene and methyl peaks (1.4–0.6 ppm) showed that 97.99% of the variance in the data is related to subject, 1.62% to sample type (serum or plasma), and 0.39% to laboratory. This interlaboratory variation is in fact smaller than the maximum acceptable intralaboratory variation on quality control samples. It is also shown that the reproducibility between laboratories is good enough for the LPD predictions to be exchangeable when the standardized NMR measurement protocol is followed. With the successful implementation of this protocol, which results in reproducible prediction of lipoprotein distributions across laboratories, a step is taken toward bringing NMR more into scope of prognostic and diagnostic biomarkers, reducing the need for less efficient methods such as ultracentrifugation or high-performance liquid chromatography (HPLC).

Integrative metabolomics as emerging tool to study autophagy regulation

Recent technological developments in metabolomics research have enabled in-depth characterization of complex metabolite mixtures in a wide range of biological, biomedical, environmental, agricultural, and nutritional research fields. Nuclear magnetic resonance spectroscopy and mass spectrometry are the two main platforms for performing metabolomics studies. Given their broad applicability and the systemic insight into metabolism that can be obtained it is not surprising that metabolomics becomes increasingly popular in basic biological research. In this review, we provide an overview on key metabolites, recent studies, and future opportunities for metabolomics in studying autophagy regulation. Metabolites play a pivotal role in autophagy regulation and are therefore key targets for autophagy research. Given the recent success of metabolomics, it can be expected that metabolomics approaches will contribute significantly to deciphering the complex regulatory mechanisms involved in autophagy in the near future and promote understanding of autophagy and autophagy-related diseases in living cells and organisms.

Whole Blood Metabolomics by 1H NMR Spectroscopy Provides a New Opportunity To Evaluate Coenzymes and Antioxidants

Conventional human blood metabolomics employs serum or plasma and provides a wealth of metabolic information therein. However, this approach lacks the ability to measure and evaluate important metabolites such as coenzymes and antioxidants that are present at high concentrations in red blood cells. As an important alternative to serum/plasma metabolomics, we show here that a simple 1H NMR experiment can simultaneously measure coenzymes and antioxidants in extracts of whole human blood, in addition to the nearly 70 metabolites that were shown to be quantitated in serum/plasma recently [ Anal. Chem. 2015 , 87 , 706 - 715 ]. Coenzymes of redox reactions: oxidized/reduced nicotinamide adenine dinucleotide (NAD+ and NADH) and nicotinamide adenine dinucleotide phosphate (NADP+ and NADPH); coenzymes of energy including adenosine triphosphate (ATP), adenosine diphosphate (ADP), and adenosine monophosphate (AMP); and antioxidants, the sum of oxidized and reduced glutathione (GSSG and GSH) can be measured with essentially no additional effort. A new method was developed for detecting many of these unstable species without affecting other blood/blood plasma metabolites. The identities of coenzymes and antioxidants in blood NMR spectra were established combining 1D/2D NMR techniques, chemical shift databases, pH measurements and, finally, spiking with authentic compounds. This is the first study to report identification of major coenzymes and antioxidants and quantify them, simultaneously, with the large pool of other metabolites in human blood using NMR spectroscopy. Considering that the levels of coenzymes and antioxidants represent a sensitive measure of cellular functions in health and numerous diseases, the NMR method presented here potentially opens a new chapter in the metabolomics of blood.

Characterizing the lipid and metabolite changes associated with placental function and pregnancy complications using ion mobility spectrometry-mass spectrometry and mass spectrometry imaging

Successful pregnancy is dependent upon discrete biological events, which include embryo implantation, decidualization, and placentation. Problems associated with each of these events can cause infertility or conditions such as preeclampsia. A greater understanding of the molecular changes associated with these complex processes is necessary to aid in identifying treatments for each condition. Previous nuclear magnetic resonance spectroscopy and mass spectrometry studies have been used to identify metabolites and lipids associated with pregnancy-related complications. However, due to limitations associated with conventional implementations of both techniques, novel technology developments are needed to more fully understand the initiation and development of pregnancy related problems at the molecular level. In this perspective, we describe current analytical techniques for metabolomic and lipidomic characterization of pregnancy complications and discuss the potential for new technologies such as ion mobility spectrometry-mass spectrometry and mass spectrometry imaging to contribute to a better understanding of the molecular changes that affect the placenta and pregnancy outcomes.

1H NMR studies on serum metabonomic changes over time in a kidney-Yang deficiency syndrome model

The central aim of this study was to investigate metabolite changes in metabolic pathwaysviametabonomic approaches in rats suffering from Kidney-Yang Deficiency Syndrome (KYDS) induced by hydrocortisone.

Recent applications of NMR in food and dietary studies

Over the last decade, a wide variety of new foods have been introduced into the global marketplace, many with health benefits that exceed those of traditional foods. Simultaneously, a wide range of analytical technologies has evolved that allow greater capability for the determination of food composition. Nuclear magnetic resonance (NMR), traditionally a research tool used for structural elucidation, is now being used frequently for metabolomics and chemical fingerprinting. Its stability and inherent ease of quantification have been exploited extensively to identify and quantify bioactive components in foods and dietary supplements. In addition, NMR fingerprints have been used to differentiate cultivars, evaluate sensory properties of food and investigate the influence of growing conditions on food crops. Here we review the latest applications of NMR in food analysis. Published 2016. This article is a U.S. Government work and is in the public domain in the USA.

Integrating ion mobility spectrometry into mass spectrometry-based exposome measurements: what can it add and how far can it go?

Measuring the exposome remains a challenge due to the range and number of anthropogenic molecules that are encountered in our daily lives, as well as the complex systemic responses to these exposures. One option for improving the coverage, dynamic range and throughput of measurements is to incorporate ion mobility spectrometry (IMS) into current MS-based analytical methods. The implementation of IMS in exposomics studies will lead to more frequent observations of previously undetected chemicals and metabolites. LC-IMS-MS will provide increased overall measurement dynamic range, resulting in detections of lower abundance molecules. Alternatively, the throughput of IMS-MS alone will provide the opportunity to analyze many thousands of longitudinal samples over lifetimes of exposure, capturing evidence of transitory accumulations of chemicals or metabolites. The volume of data corresponding to these new chemical observations will almost certainly outpace the generation of reference data to enable their confident identification. In this perspective, we briefly review the state-of-the-art in measuring the exposome, and discuss the potential use for IMS-MS and the physico-chemical property of collisional cross section in both exposure assessment and molecular identification.

Comprehensive Metabolite Identification Strategy Using Multiple Two-Dimensional NMR Spectra of a Complex Mixture Implemented in the COLMARm Web Server

Identification of metabolites in complex mixtures represents a key step in metabolomics. A new strategy is introduced, which is implemented in a new public web server, COLMARm, that permits the coanalysis of up to three two-dimensional (2D) NMR spectra, namely, ¹³C-¹H HSQC (heteronuclear single quantum coherence spectroscopy), ¹H-¹H TOCSY (total correlation spectroscopy), and ¹³C-¹H HSQC-TOCSY, for the comprehensive, accurate, and efficient performance of this task. The highly versatile and interactive nature of COLMARm permits its application to a wide range of metabolomics samples independent of the magnetic field. Database query is performed using the HSQC spectrum, and the top metabolite hits are then validated against the TOCSY-type experiment(s) by superimposing the expected cross-peaks on the mixture spectrum. In this way the user can directly accept or reject candidate metabolites by taking advantage of the complementary spectral information offered by these experiments and their different sensitivities. The power of COLMARm is demonstrated for a human serum sample uncovering the existence of 14 metabolites that hitherto were not identified by NMR.

A Comparative Metabolomics Approach Reveals Early Biomarkers for Metabolic Response to Acute Myocardial Infarction

Discovery of novel biomarkers is critical for early diagnosis of acute coronary syndrome (ACS). Serum metabolite profiling of ST-elevation myocardial infarction (STEMI), unstable angina (UA) and healthy controls was performed using gas chromatography mass spectrometry (GC/MS), solid-phase microextraction coupled to gas chromatography mass spectrometry (SPME-GC/MS) and nuclear magnetic resonance (¹H-NMR). Multivariate data analysis revealed a metabolic signature that could robustly discriminate STEMI patients from both healthy controls and UA patients. This panel of biomarkers consisted of 19 metabolites identified in the serum of STEMI patients. One of the most intriguing biomarkers among these metabolites is hydrogen sulfide (H₂S), an endogenous gasotransmitter with profound effect on the heart. Serum H₂S absolute levels were further investigated using a quantitative double-antibody sandwich enzyme-linked immunosorbent assay (ELISA). This highly sensitive immunoassay confirmed the elevation of serum H₂S in STEMI patients. H₂S level discriminated between UA and STEMI groups, providing an initial insight into serum-free H₂S bioavailability during ACS. In conclusion, the current study provides a detailed map illustrating the most predominant altered metabolic pathways and the biochemical linkages among the biomarker metabolites identified in STEMI patients. Metabolomics analysis may yield novel predictive biomarkers that will potentially allow for an earlier medical intervention.

Nuclear Magnetic Resonance-Based Metabolomics of Human Filtered Serum: A Great White Hope in Appraisal of Chronic Stable Angina and Myocardial Infarction

BACKGROUND

Biochemical detection of chronic stable angina (CSA) and myocardial infarction (MI) are challenging. To address the shortcomings of the conventional biochemical approach for detection of MI, we applied serum lacking proteins and lipoprotein-based metabolomics in an approach using proton nuclear magnetic resonance (1H NMR) spectroscopy for screening of coronary artery disease (CAD) and especially MI. Our aim was to discover differential biomarkers among subjects with normal coronary (NC), CSA, and MI.

METHODS

The study comprised serum samples from nondiabetic angiographically proven CAD [CSA (n = 88), MI (n = 90)] and NC (n = 55). 1H NMR spectroscopy was used to acquire metabolomics data. Clinical variables such as troponin I (TI), lactate dehydrogenase (LD), creatine kinase (CK, CK-MB, CK-MM), serum creatinine, and lipid profiles were also measured in all subjects. Metabolomic data and clinical measures were appraised separately using a chemometric approach and ROC analysis.

RESULTS

The screening outcomes revealed that the pattern of methylguanidine, lactate, creatinine, threonine, aspartate, and trimethylamine (TMA), and TI, LD, CK, and serum creatinine were changed in CAD compared to NC. Statistical analysis demonstrated high precision (93.6% by NMR and 67.4% by clinical measures) to distinguish CAD from NC. Further analysis indicated that methylguanidine, arginine, and threonine, and TI, LD, and serum creatinine were significantly changed in CSA compared to MI. Statistical analysis demonstrated high accuracy (88.2% by NMR and 92.1% by clinical measures) to discriminate CSA from MI.

CONCLUSIONS

In contrast to other laboratory methods, 1H NMR-based metabolomics of filtered sera appears to be a robust, rapid, and minimally invasive approach to probe CSA and MI.

Pathophysiologic processes have an impact on the plasma metabolomic signature of endometriosis patients

OBJECTIVE

To evaluate potential variations in the plasma metabolomic profile of endometriosis patients as a consequence of pathophysiologic alterations associated with this disorder.

DESIGN

Prospective study. For each subject, a plasma sample was collected after overnight fasting and before surgery.

SETTING

University medical center.

PATIENT(S)

The clinical cohort included 50 endometriosis patients, diagnosed at early (n = 6) and advanced (n = 44) stages of the disease, and 23 healthy women. All volunteers underwent diagnostic laparoscopy to visually confirm the presence or absence of endometriotic lesions.

INTERVENTION(S)

Metabolomic profiling of plasma samples based on ¹H-nuclear magnetic resonance (NMR) spectroscopy in combination with statistical approaches.

MAIN OUTCOME MEASURE(S)

Comparative identification of metabolites present in plasma from endometriosis patients and healthy women.

RESULT(S)

The plasma metabolomic profile of endometriosis patients was characterized by increased concentration of valine, fucose, choline-containing metabolites, lysine/arginine, and lipoproteins and decreased concentration of creatinine compared with healthy women. Metabolic alterations identified in the plasma metabolomic profile of endometriosis patients correlate with pathophysiologic events previously described in the progression of this disease.

CONCLUSION(S)

The results highlight the potential of ¹H-NMR-based metabolomics to characterize metabolic alterations associated with endometriosis in plasma samples. This information could be useful to get a better understanding of the molecular mechanisms involved in the pathogenesis of endometriosis, thus facilitating the noninvasive diagnosis of this pathology at early stages.

Screening the low molecular weight fraction of human serum using ATR-IR spectroscopy

Vibrational spectroscopic techniques can detect small variations in molecular content, linked with disease, showing promise for screening and early diagnosis. Biological fluids, particularly blood serum, are potentially valuable for diagnosis purposes. The so-called Low Molecular Weight Fraction (LMWF) contains the associated peptidome and metabolome and has been identified as potentially the most relevant molecular population for disease-associated biomarker research. Although vibrational spectroscopy can deliver a specific chemical fingerprint of the samples, the High Molecular Weight Fraction (HMWF), composed of the most abundant serum proteins, strongly dominates the response and ultimately makes the detection of minor spectral variations a challenging task. Spectroscopic detection of potential serum biomarkers present at relatively low concentrations can be improved using pre-analytical depletion of the HMWF. In the present study, human serum fractionation by centrifugal filtration was used prior to analysis by Attenuated Total Reflection infrared spectroscopy. Using a model sample based on glycine spiked serum, it is demonstrated that the screening of the LMWF can be applied to quantify blinded concentrations up to 50 times lower. Moreover, the approach is easily transferable to different bodily fluids which would support the development of more efficient and suitable clinical protocols exploring vibrational spectroscopy based ex-vivo diagnostic tools. Revealing serum LMWF for spectral serological diagnostic applications.

NMR spectroscopy of filtered serum of prostate cancer: A new frontier in metabolomics

BACKGROUND

To address the shortcomings of digital rectal examinations (DRE), serum prostate-specific antigen (PSA), and trans-rectal ultrasound (TRUS) for precise determination of prostate cancer (PC) and differentiation from benign prostatic hyperplasia (BPH), we applied (1) H-nuclear magnetic resonance (NMR) spectroscopy as a surrogate tactic for probing and prediction of PC and BPH.

METHODS

The study comprises 210 filtered sera from suspected PC, BPH, and a healthy subjects' cohort (HC). The filtered serum approach delineates to identify and quantify 52 metabolites using (1) H NMR spectroscopy. All subjects had undergone clinical evaluations (DRE, PSA, and TRUS) followed by biopsy for Gleason score, if needed. NMR-measured metabolites and clinical evaluation data were examined separately using linear multivariate discriminant function analysis (DFA) to probe the signature descriptors for each cohort.

RESULTS

DFA indicated that glycine, sarcosine, alanine, creatine, xanthine, and hypoxanthine were able to determine abnormal prostate (BPH + PC). DFA-based classification presented high precision (86.2% by NMR and 68.1% by clinical laboratory method) in discriminating HC from BPH + PC. DFA reveals that alanine, sarcosine, creatinine, glycine, and citrate were able to discriminate PC from BPH. DFA-based categorization exhibited high accuracy (88.3% by NMR and 75.2% by clinical laboratory method) to differentiate PC from BPH.

CONCLUSIONS

(1) H NMR-based metabolic profiling of filtered-serum sample appears to be assuring, swift, and least-invasive for probing and prediction of PC and BPH with its signature metabolic profile. This novel technique is not only on a par with histopathological evaluation of PC determination but is also comparable to liquid chromatography-based mass spectrometry to identify the metabolites. Prostate 76:1106-1119, 2016. © 2016 Wiley Periodicals, Inc.

The future of NMR-based metabolomics

The two leading analytical approaches to metabolomics are mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy. Although currently overshadowed by MS in terms of numbers of compounds resolved, NMR spectroscopy offers advantages both on its own and coupled with MS. NMR data are highly reproducible and quantitative over a wide dynamic range and are unmatched for determining structures of unknowns. NMR is adept at tracing metabolic pathways and fluxes using isotope labels. Moreover, NMR is non-destructive and can be utilized in vivo. NMR results have a proven track record of translating in vitro findings to in vivo clinical applications.

Assessment of dietary exposure and effect in humans: The role of NMR

In human nutritional science progress has always depended strongly on analytical measurements for establishing relationships between diet and health. This field has undergone significant changes as a result of the development of NMR and mass spectrometry methods for large scale detection, identification and quantification of metabolites in body fluids. This has allowed systematic studies of the metabolic fingerprints that biological processes leave behind, and has become the research field of metabolomics. As a metabolic profiling technique, NMR is at its best when its unbiased nature, linearity and reproducibility are exploited in well-controlled nutritional intervention and cross-sectional population screening studies. Although its sensitivity is less good than that of mass spectrometry, NMR has maintained a strong position in metabolomics through implementation of standardisation protocols, hyphenation with mass spectrometry and chromatographic techniques, accurate quantification and spectral deconvolution approaches, and high-throughput automation. Thus, NMR-based metabolomics has contributed uniquely to new insights into dietary exposure, in particular by unravelling the metabolic fates of phytochemicals and the discovery of dietary intake markers. NMR profiling has also contributed to the understanding of the subtle effects of diet on central metabolism and lipoprotein metabolism. In order to hold its ground in nutritional metabolomics, NMR will need to step up its performance in sensitivity and resolution; the most promising routes forward are the analytical use of dynamic nuclear polarisation and developments in microcoil construction and automated fractionation.

Combining NMR and LC/MS Using Backward Variable Elimination: Metabolomics Analysis of Colorectal Cancer, Polyps, and Healthy Controls

Both nuclear magnetic resonance (NMR) spectroscopy and mass spectrometry (MS) play important roles in metabolomics. The complementary features of NMR and MS make their combination very attractive; however, currently the vast majority of metabolomics studies use either NMR or MS separately, and variable selection that combines NMR and MS for biomarker identification and statistical modeling is still not well developed. In this study focused on methodology, we developed a backward variable elimination partial least-squares discriminant analysis algorithm embedded with Monte Carlo cross validation (MCCV-BVE-PLSDA), to combine NMR and targeted liquid chromatography (LC)/MS data. Using the metabolomics analysis of serum for the detection of colorectal cancer (CRC) and polyps as an example, we demonstrate that variable selection is vitally important in combining NMR and MS data. The combined approach was better than using NMR or LC/MS data alone in providing significantly improved predictive accuracy in all the pairwise comparisons among CRC, polyps, and healthy controls. Using this approach, we selected a subset of metabolites responsible for the improved separation for each pairwise comparison, and we achieved a comprehensive profile of altered metabolite levels, including those in glycolysis, the TCA cycle, amino acid metabolism, and other pathways that were related to CRC and polyps. MCCV-BVE-PLSDA is straightforward, easy to implement, and highly useful for studying the contribution of each individual variable to multivariate statistical models. On the basis of these results, we recommend using an appropriate variable selection step, such as MCCV-BVE-PLSDA, when analyzing data from multiple analytical platforms to obtain improved statistical performance and a more accurate biological interpretation, especially for biomarker discovery. Importantly, the approach described here is relatively universal and can be easily expanded for combination with other analytical technologies.

Research Priorities in the Field of Posttraumatic Pain and Disability: Results of a Transdisciplinary Consensus-Generating Workshop

Background. Chronic or persistent pain and disability following noncatastrophic “musculoskeletal” (MSK) trauma is a pervasive public health problem. Recent intervention trials have provided little evidence of benefit from several specific treatments for preventing chronic problems. Such findings may appear to argue against formal targeted intervention for MSK traumas. However, these negative findings may reflect a lack of understanding of the causal mechanisms underlying the transition from acute to chronic pain, rendering informed and objective treatment decisions difficult. The Canadian Institutes of Health Research (CIHR) Institute of Musculoskeletal Health and Arthritis (IMHA) has recently identified better understanding of causal mechanisms as one of three priority foci of their most recent strategic plan. Objectives. A 2-day invitation-only active participation workshop was held in March 2015 that included 30 academics, clinicians, and consumers with the purpose of identifying consensus research priorities in the field of trauma-related MSK pain and disability, prediction, and prevention. Methods. Conversations were recorded, explored thematically, and member-checked for accuracy. Results. From the discussions, 13 themes were generated that ranged from a focus on identifying causal mechanisms and models to challenges with funding and patient engagement. Discussion. Novel priorities included the inclusion of consumer groups in research from the early conceptualization and design stages and interdisciplinary longitudinal studies that include evaluation of integrated phenotypes and mechanisms.

Simultaneous Analysis of Major Coenzymes of Cellular Redox Reactions and Energy Using ex Vivo (1)H NMR Spectroscopy

Coenzymes of cellular redox reactions and cellular energy mediate biochemical reactions fundamental to the functioning of all living cells. Despite their immense interest, no simple method exists to gain insights into their cellular concentrations in a single step. We show that a simple (1)H NMR experiment can simultaneously measure oxidized and reduced forms of nicotinamide adenine dinucleotide (NAD(+) and NADH), oxidized and reduced forms of nicotinamide adenine dinucleotide phosphate (NADP(+) and NADPH), and adenosine triphosphate (ATP) and its precursors, adenosine diphosphate (ADP) and adenosine monophosphate (AMP), using mouse heart, kidney, brain, liver, and skeletal muscle tissue extracts as examples. Combining 1D/2D NMR experiments, chemical shift libraries, and authentic compound data, reliable peak identities for these coenzymes have been established. To assess this methodology, cardiac NADH and NAD(+) ratios/pool sizes were measured using mouse models with a cardiac-specific knockout of the mitochondrial Complex I Ndufs4 gene (cKO) and cardiac-specific overexpression of nicotinamide phosphoribosyltransferase (cNAMPT) as examples. Sensitivity of NAD(+) and NADH to cKO or cNAMPT was observed, as anticipated. Time-dependent investigations showed that the levels of NADH and NADPH diminish by up to ∼50% within 24 h; concomitantly, NAD(+) and NADP(+) increase proportionately; however, degassing the sample and flushing the sample tubes with helium gas halted such changes. The analysis protocol along with the annotated characteristic fingerprints for each coenzyme is provided for easy identification and absolute quantification using a single internal reference for routine use. The ability to visualize the ubiquitous coenzymes fundamental to cellular functions, simultaneously and reliably, offers a new avenue to interrogate the mechanistic details of cellular function in health and disease.

A simple and accurate protocol for absolute polar metabolite quantification in cell cultures using quantitative nuclear magnetic resonance

Absolute analyte quantification by nuclear magnetic resonance (NMR) spectroscopy is rarely pursued in metabolomics, even though this would allow researchers to compare results obtained using different techniques. Here we report on a new protocol that permits, after pH-controlled serum protein removal, the sensitive quantification (limit of detection [LOD] = 5-25 μM) of hydrophilic nutrients and metabolites in the extracellular medium of cells in cultures. The method does not require the use of databases and uses PULCON (pulse length-based concentration determination) quantitative NMR to obtain results that are significantly more accurate and reproducible than those obtained by CPMG (Carr-Purcell-Meiboom-Gill) sequence or post-processing filtering approaches. Three practical applications of the method highlight its flexibility under different cell culture conditions. We identified and quantified (i) metabolic differences between genetically engineered human cell lines, (ii) alterations in cellular metabolism induced by differentiation of mouse myoblasts into myotubes, and (iii) metabolic changes caused by activation of neurotransmitter receptors in mouse myoblasts. Thus, the new protocol offers an easily implementable, efficient, and versatile tool for the investigation of cellular metabolism and signal transduction.

Serum nuclear magnetic resonance-based metabolomics and outcome in diffuse large B-cell lymphoma patients - a pilot study

The prognosis for diffuse large B-cell lymphoma (DLBCL) patients with early relapse or refractory disease is dismal. To determine if clinical outcome correlated to diverse serum metabolomic profiles, we used (1)H nuclear magnetic resonance (NMR) spectroscopy and compared two groups of DLBCL patients treated with immunochemotherapy: i) refractory/early relapse (REF/REL; n=27) and ii) long-term progression-free (CURED; n = 60). A supervised multivariate analysis showed a separation between the groups. Among discriminating metabolites higher in the REF/REL group were the amino acids lysine and arginine, the degradation product cadaverine and a compound in oxidative stress (2-hydroxybutyrate). In contrast, the amino acids aspartate, valine and ornithine, and a metabolite in the glutathione cycle, pyroglutamate, were higher in CURED patients. Together, our data indicate that NMR-based serum metabolomics can identify a signature for DLBCL patients with high-risk of failing immunochemotherapy, prompting for larger validating studies which could lead to more individualized treatment of this disease.

Applications of NMR spectroscopy to systems biochemistry

The past decades of advancements in NMR have made it a very powerful tool for metabolic research. Despite its limitations in sensitivity relative to mass spectrometric techniques, NMR has a number of unparalleled advantages for metabolic studies, most notably the rigor and versatility in structure elucidation, isotope-filtered selection of molecules, and analysis of positional isotopomer distributions in complex mixtures afforded by multinuclear and multidimensional experiments. In addition, NMR has the capacity for spatially selective in vivo imaging and dynamical analysis of metabolism in tissues of living organisms. In conjunction with the use of stable isotope tracers, NMR is a method of choice for exploring the dynamics and compartmentation of metabolic pathways and networks, for which our current understanding is grossly insufficient. In this review, we describe how various direct and isotope-edited 1D and 2D NMR methods can be employed to profile metabolites and their isotopomer distributions by stable isotope-resolved metabolomic (SIRM) analysis. We also highlight the importance of sample preparation methods including rapid cryoquenching, efficient extraction, and chemoselective derivatization to facilitate robust and reproducible NMR-based metabolomic analysis. We further illustrate how NMR has been applied in vitro, ex vivo, or in vivo in various stable isotope tracer-based metabolic studies, to gain systematic and novel metabolic insights in different biological systems, including human subjects. The pathway and network knowledge generated from NMR- and MS-based tracing of isotopically enriched substrates will be invaluable for directing functional analysis of other 'omics data to achieve understanding of regulation of biochemical systems, as demonstrated in a case study. Future developments in NMR technologies and reagents to enhance both detection sensitivity and resolution should further empower NMR in systems biochemical research.

Recommendations and Standardization of Biomarker Quantification Using NMR-Based Metabolomics with Particular Focus on Urinary Analysis

NMR-based metabolomics has shown considerable promise in disease diagnosis and biomarker discovery because it allows one to nondestructively identify and quantify large numbers of novel metabolite biomarkers in both biofluids and tissues. Precise metabolite quantification is a prerequisite to move any chemical biomarker or biomarker panel from the lab to the clinic. Among the biofluids commonly used for disease diagnosis and prognosis, urine has several advantages. It is abundant, sterile, and easily obtained, needs little sample preparation, and does not require invasive medical procedures for collection. Furthermore, urine captures and concentrates many "unwanted" or "undesirable" compounds throughout the body, providing a rich source of potentially useful disease biomarkers; however, incredible variation in urine chemical concentrations makes analysis of urine and identification of useful urinary biomarkers by NMR challenging. We discuss a number of the most significant issues regarding NMR-based urinary metabolomics with specific emphasis on metabolite quantification for disease biomarker applications and propose data collection and instrumental recommendations regarding NMR pulse sequences, acceptable acquisition parameter ranges, relaxation effects on quantitation, proper handling of instrumental differences, sample preparation, and biomarker assessment.