Search

BACKGROUND: The associations of red and processed meat with chronic disease risk remain to be clarified, in part because of measurement error in self-reported diet. OBJECTIVES: We sought to develop metabolomics-based biomarkers for red and processed meat, and to evaluate associations of biomarker-calibrated meat intake with chronic disease risk among postmenopausal women. METHODS: Study participants were women who were members of the Women's Health Initiative (WHI) study cohorts. These participants were postmenopausal women aged 50–79 y when enrolled during 1993–1998 at 40 US clinical centers with embedded human feeding and nutrition biomarker studies. Literature reports of metabolomics correlates of meat consumption were used to develop meat intake biomarkers from serum and 24-h urine metabolites in a 153-participant feeding study (2010–2014). Resulting biomarkers were used in a 450-participant biomarker study (2007–2009) to develop linear regression calibration equations that adjust FFQ intakes for random and systematic measurement error. Biomarker-calibrated meat intakes were associated with cardiovascular disease, cancer, and diabetes incidence among 81,954 WHI participants (1993–2020). RESULTS: Biomarkers and calibration equations meeting prespecified criteria were developed for consumption of red meat and red plus processed meat combined, but not for processed meat consumption. Following control for nondietary confounding factors, hazard ratios were calculated for a 40% increment above the red meat median intake for coronary artery disease (HR: 1.10; 95% CI: 1.07, 1.14), heart failure (HR: 1.26; 95% CI: 1.20, 1.33), breast cancer (HR: 1.10; 95% CI: 1.07, 1.13) for, total invasive cancer (HR: 1.07; 95% CI: 1.05, 1.09), and diabetes (HR: 1.37; 95% CI: 1.34, 1.39). HRs for red plus processed meat intake were similar. HRs were close to the null, and mostly nonsignificant following additional control for dietary potential confounding factors, including calibrated total energy consumption. CONCLUSIONS: A relatively high-meat dietary pattern is associated with somewhat higher chronic disease risks. These elevations appear to be largely attributable to the dietary pattern, rather than to consumption of red or processed meat per se.

Human blood is the most widely used biospecimen in the clinic and the metabolomics field. While both mass spectrometry and NMR spectroscopy are the two premier analytical platforms in the metabolomics field, NMR exhibits several unsurpassed characteristics for blood metabolite analysis, the most important of which are its ability to identify unknown metabolites and its quantitative nature. However, the relatively small number of metabolites accessible by NMR has restricted the scope of its applications. Enhancing the limit of identified metabolites in blood will therefore greatly impact NMR-based metabolomics. Continuing our efforts to address this major issue, our current study describes the identification of 12 metabolites, which expands the number of quantifiable blood metabolites by ~15%. These results, in combination with our earlier efforts, now provide access to nearly 90 metabolites, which is the highest to date for a simple 1D

Nuclear Magnetic Resonance (NMR) spectroscopy is one of the two major analytical platforms in the field of metabolomics, the other being mass spectrometry (MS). NMR is less sensitive than MS and hence it detects a relatively small number of metabolites. However, NMR exhibits numerous unique characteristics including its high reproducibility and non-destructive nature, its ability to identify unknown metabolites definitively, and its capabilities to obtain absolute concentrations of all detected metabolites, sometimes even without an internal standard. These characteristics outweigh the relatively low sensitivity and resolution of NMR in metabolomics applications. Since biological mixtures are highly complex, increased demand for new methods to improve detection, better identify unknown metabolites, and provide more accurate quantitation continues unabated. Technological and methodological advances to date have helped to improve the resolution and sensitivity and detection of a larger number of metabolite signals. Efforts focused on measuring unknown metabolite signals have resulted in the identification and quantitation of an expanded pool of metabolites including labile metabolites such as cellular redox coenzymes, energy coenzymes, and antioxidants. This chapter describes quantitative NMR methods in metabolomics with an emphasis on recent methodological developments, while highlighting the benefits and challenges of NMR-based metabolomics.

Background Knowledge about macronutrient intake and chronic disease risk has been limited by the absence of objective macronutrient measures. Recently, we proposed novel biomarkers for protein, protein density, carbohydrate, and carbohydrate density, using established biomarkers and serum and urine metabolomics profiles in a human feeding study. Objectives We aimed to use these biomarkers to develop calibration equations for macronutrient variables using dietary self-reports and personal characteristics and to study the association between biomarker-calibrated intake estimates and cardiovascular disease, cancer, and diabetes risk in Women's Health Initiative (WHI) cohorts. Methods Prospective disease association analyses are based on WHI cohorts of postmenopausal US women aged 50-79 y when enrolled at 40 US clinical centers (n = 81,954). We used biomarker intake values in a WHI nutritional biomarker study (n = 436) to develop calibration equations for each macronutrient variable, leading to calibrated macronutrient intake estimates throughout WHI cohorts. We then examined the association of these intakes with chronic disease incidence over a 20-y (median) follow-up period using HR regression methods. Results In analyses that included doubly labeled water-calibrated total energy, HRs for cardiovascular diseases and cancers were mostly unrelated to calibrated protein density. However, many were inversely related to carbohydrate density, with HRs (95% CIs) for a 20% increment in carbohydrate density of 0.81 (0.69, 0.95) and 0.83 (0.74, 0.93), respectively, for primary outcomes of coronary heart disease and breast cancer, as well as 0.74 (0.60, 0.91) and 0.87 (0.81, 0.93) for secondary outcomes of heart failure and total invasive cancer. Corresponding HRs (95% CIs) for type 2 diabetes incidence in relation to protein density and carbohydrate density were 1.17 (1.09, 1.75) and 0.73 (0.66, 0.80), respectively. Conclusions At specific energy intake, a diet high in carbohydrate density is associated with substantially reduced risk of major chronic diseases in a population of US postmenopausal women. This trial was registered at clinicaltrials.gov as NCT00000611.

Significant advances have been made in unknown metabolite identification and expansion of the number of quantifiable metabolites in human plasma, serum, and whole blood using NMR spectroscopy. However, reliable quantitation of metabolites is still a challenge. A major bottleneck is the lack of a suitable internal standard that does not interact with the complex blood sample matrix and also does not overlap with metabolite peaks apart from exhibiting other favorable characteristics. With the goal of addressing this challenge, a comprehensive investigation of fumaric and maleic acids as potential internal standards was made along with a comparison with the conventional standards, TSP (trimethylsilylpropionic acid) and DSS (trimethylsilylpropanesulfonic acid). Both fumaric acid and maleic acid exhibited a surprisingly high performance with a quantitation error

Nicotinamide adenine dinucleotide (NAD

BACKGROUND: We recently developed protein and carbohydrate intake biomarkers using metabolomics profiles in serum and urine, and used them to correct self-reported dietary data for measurement error. Biomarker-calibrated carbohydrate density was inversely associated with chronic disease risk, whereas protein density associations were mixed. OBJECTIVES: To elucidate and extend this earlier work through biomarker development for protein and carbohydrate components, including animal protein and fiber. METHODS: Prospective disease association analyses were undertaken in Women's Health Initiative (WHI) cohorts of postmenopausal US women, aged 50–79 y when enrolled at 40 US clinical centers. Biomarkers were developed using an embedded human feeding study (n = 153). Calibration equations for protein and carbohydrate components were developed using a WHI nutritional biomarker study (n = 436). Calibrated intakes were associated with chronic disease incidence in WHI cohorts (n = 81,954) over a 20-y (median) follow-up period, using HR regression methods. RESULTS: Previously reported elevations in cardiovascular disease (CVD) with higher-protein diets tended to be explained by animal protein density. For example, for coronary heart disease a 20% increment in animal protein density had an HR of 1.20 (95% CI: 1.02, 1.42) relative to the HR for total protein density. In comparison, cancer and diabetes risk showed little association with animal protein density beyond that attributable to total protein density. Inverse carbohydrate density associations with total CVD were mostly attributable to fiber density, with a 20% increment HR factor of 0.89 (95% CI: 0.83, 0.94). Cancer risk showed little association with fiber density, whereas diabetes risk had a 20% increment HR of 0.93 (95% CI: 0.88, 0.98) relative to the HRs for total carbohydrate density. CONCLUSIONS: In a population of postmenopausal US women, CVD risk was associated with high-animal-protein and low-fiber diets, cancer risk was associated with low-carbohydrate diets, and diabetes risk was associated with low-fiber/low-carbohydrate diets.

Glutathione is a ubiquitous cellular antioxidant, which is critically required to protect cells from oxidative damage and free radical injury. It is practically impossible to analyze glutathione in its native form after isolation from biological mixtures since the active form (reduced glutathione, GSH) spontaneously gets converted to the oxidized form (oxidized glutathione, GSSG). To address this challenge, numerous highly sensitive detection methods, including mass spectrometry, have been used in conjunction with derivatization to block the oxidation of GSH. Efforts so far to quantitate GSH and GSSG using the nuclear magnetic resonance (NMR) spectroscopy method have remained unsuccessful. With a focus on addressing this challenge, in this study, we describe an extension to our recent whole blood analysis method [ Anal. Chem. 2017, 89, 4620-4627] that includes the important antioxidants GSH and GSSG. Fresh and frozen human whole blood specimens as well as standard GSH and GSSG were comprehensively investigated using NMR without and with derivatization using N-ethylmaleimide (NEM). NMR experiments detect two diastereomers, distinctly, for the derivatized GSH and enable the analysis of both GSH and GSSG in human whole blood with an accuracy of >99%. Interestingly, the excess (unreacted) NEM used for blocking the GSH can be removed from the samples during a drying step after extraction, with no need for additional processing. This is an important characteristic that offers an added advantage for simultaneous analysis of the antioxidants (GSH and GSSG), redox coenzymes (oxidized nicotinamide adenine dinucleotide (NAD+), reduced nicotinamide adenine dinucleotide (NADH), oxidized nicotinamide adenine dinucleotide phosphate (NADP+), reduced nicotinamide adenine dinucleotide phosphate (NADPH)), energy coenzymes (adenosine 5'-triphosphate (ATP), adenosine 5'-diphosphate (ADP), adenosine 5'-monophosphate (AMP)), and a large number of other blood metabolites using the same one-dimensional (1D) NMR spectrum. The presented method broadens the scope of global metabolite profiling and adds a new dimension to NMR-based blood metabolomics. Further, the method demonstrated here for human blood can be extended to virtually any biological specimen.

Absolute quantitation is a major challenge in metabolomics. Previously, we [ Nagana Gowda et al. Anal. Chem. 2018 , 90 , 2001 - 2009 ] showed that nuclear magnetic resonance (NMR) spectroscopy can guide absolute quantitation using mass spectrometry (MS); however, this method does not account for the matrix effect in MS measurements. To surmount this challenge, we have developed a novel method, qNMR-MS, for the absolute quantitation of metabolites using MS by combining it with NMR and chemical derivatization. Metabolite concentrations are first obtained using NMR for a reference sample. Subsequently, both reference and study samples are chemically derivatized with isotope-labeled and unlabeled reagents, respectively. The derivatized reference sample is then mixed with study samples and measured using MS. Comparison of paired isotope unlabeled and labeled MS peaks enables absolute quantitation with virtually no matrix effects. As a proof of concept, we applied the qNMR-MS method for absolute quantitation of amino acids using propyl-chloroformate (PCF) derivatization. For standards, the observed coefficients of determination ( R2) of most amino acids were greater than 0.99 across concentrations of 0.2 to 20 uM. For human serum, the results of the qNMR-MS method are comparable to the conventional isotope-labeled internal standard (iSTD) method ( R2 ≥ 0.99), with an average median coefficient of variation (CV) of 5.45%. The qNMR-MS method is relatively simple, highly quantitative, has high cost-efficiency (no iSTD required), and offers new avenues for the routine quantitation of amino acids in blood samples; it can, in principle, be extended to a wide variety of metabolites in different biological samples.

Coenzyme A (CoA) and acetyl-coenzyme A (acetyl-CoA) are ubiquitous cellular molecules, which mediate hundreds of anabolic and catabolic reactions including energy metabolism. Highly sensitive methods including absorption spectroscopy and mass spectrometry enable their analysis, albeit with many limitations. To date, however, NMR spectroscopy has not been used to analyze these important molecules. Building on our recent efforts, which enabled simultaneous analysis of a large number of metabolites in tissue and blood including many coenzymes and antioxidants [Anal Chem. 2016, 88:4817–24; ibid 2017, 89:4620–4627], we describe here a new method for identification and quantitation of CoA and acetyl-CoA ex vivo in tissue. Using mouse heart, kidney, liver, brain and skeletal tissue, we show that a simple (1)H NMR experiment can simultaneously measure these molecules. Identification of the two species involved a comprehensive analysis of the different tissue types using 1D and 2D NMR, in combination with spectral databases for standards, as well as spiking with authentic compounds. Time dependent studies showed that while the acetyl-CoA levels remain unaltered, CoA levels diminish by more than 50% within 24 h, which indicates that CoA is labile in solution; however, degassing the sample with helium gas halted its oxidation. Further, interestingly, we also identified endogenous coenzyme A glutathione disulfide (CoA-S-S-G) in tissue for the first time by NMR and show that CoA, when oxidized in tissue extract also forms the same disulfide metabolite. The new ability to simultaneously visualize absolute concentrations of CoA, acetyl-CoA and endogenous CoA-S-S-G along with redox coenzymes (NAD(+), NADH, NADP(+), NADPH), energy coenzymes (ATP, ADP, AMP), antioxidants (GSH, GSSG) and a vast pool of other metabolites using a single 1D NMR spectrum offers a new avenue in the metabolomics field for investigation of cellular function in health and disease.

Nuclear magnetic resonance (NMR) spectroscopy is a major analytical method used in the growing field of metabolomics. Although NMR is relatively less sensitive than mass spectrometry, this analytical platform has numerous characteristics including its high reproducibility and quantitative abilities, its nonselective and noninvasive nature, and the ability to identify unknown metabolites in complex mixtures and trace the downstream products of isotope labeled substrates ex vivo, in vivo, or in vitro. Metabolomic analysis of highly complex biological mixtures has benefitted from the advances in both NMR data acquisition and analysis methods. Although metabolomics applications span a wide range of disciplines, a majority has focused on understanding, preventing, diagnosing, and managing human diseases. This chapter describes NMR-based methods relevant to the rapidly expanding metabolomics field.

PURPOSE: Objective biomarkers of dietary exposure are needed to establish reliable diet-disease associations. Unfortunately, robust biomarkers of macronutrient intakes are scarce. We aimed to assess the utility of serum, 24-hour urine and spot urine high-dimensional metabolites for the development of biomarkers of daily intake of total energy, protein, carbohydrate and fat, and the percent of energy from these macronutrients (%E). METHODS: A 2-week controlled feeding study mimicking the participants’ habitual diets was conducted among 153 postmenopausal women from the Women’s Health Initiative (WHI). Fasting serum metabolomic profiles were analyzed using a targeted liquid chromatography-tandem mass spectrometry (LC-MS/MS) assay for aqueous metabolites and a direct injection based quantitative lipidomics platform. Urinary metabolites were analyzed using (1)H nuclear magnetic resonance (NMR) spectroscopy at 800 MHz and by untargeted gas chromatography-mass spectrometry (GC-MS). Variable selection was performed to build prediction models for each dietary variable. RESULTS: The highest cross-validated multiple correlation coefficients (CV-R(2)) for protein intake (%E) and carbohydrate intake (%E) using metabolites only were 36.3% and 37.1% respectively. With the addition of established dietary biomarkers (doubly labeled water for energy and urinary nitrogen for protein), the CV-R(2) reached 55.5% for energy (kcal/d), 52.0% and 45.0% for protein (g/d, %E), 55.9% and 37.0% for carbohydrate (g/d, %E). CONCLUSION: Selected panels of serum and urine metabolites, without the inclusion of doubly labeled water and urinary nitrogen biomarkers, gives a reliable and robust prediction of daily intake of energy from protein and carbohydrate.

Background and objective Metabolomics deals with the identification and quantification of small molecules (metabolites) in biological samples. As metabolite levels can reflect normal or altered metabolic pathways, their measurement provides information to improve the understanding, diagnosis and management of diseases. Despite its immense potential, metabolomics applications to pain research have been sparse. This paper describes current metabolomics techniques, reviews published human metabolomics pain research and compares successful metabolomics research in other areas of medicine with the goal of highlighting opportunities offered by metabolomics to advance pain medicine. Databases and data treatment Non-systematic review. Results Our search identified 19 studies that adopted a metabolomics approach in: fibromyalgia (7), chronic widespread pain (4), other musculoskeletal pain conditions (5), neuropathic pain (1), complex regional pain syndrome (1) and pelvic pain (1). The studies used either mass spectrometry or nuclear magnetic resonance. Most are characterized by small sample sizes. Some consistency has been found for alterations in glutamate and testosterone metabolism, and metabolic imbalances caused by the gut microbiome. Conclusions Metabolomics research in chronic pain is in its infancy. Most studies are at the pilot stage. Metabolomics research has been successful in other areas of medicine. These achievements should motivate investigators to expand metabolomics research to improve the understanding of the basic mechanisms of human pain, as well as provide tools to diagnose, predict and monitor chronic pain conditions. Metabolomics research can lead to the identification of biomarkers to support the development and testing of treatments, thereby facilitating personalized pain medicine.

Nonalcoholic fatty liver disease (NAFLD) is categorized based on histological severity into nonalcoholic fatty liver (NAFL) or nonalcoholic steatohepatitis (NASH). We used a multiplatform metabolomics approach to identify metabolite markers and metabolic pathways that distinguish NAFL from early NASH and advanced NASH. We analyzed fasting serum samples from 57 prospectively-recruited patients with histologically-proven NAFLD, including 12 with NAFL, 31 with early NASH and 14 with advanced NASH. Metabolite profiling was performed using a combination of liquid chromatography-mass spectrometry (LC-MS) and nuclear magnetic resonance (NMR) spectroscopy analyzed with multivariate statistical and pathway analysis tools. We targeted 237 metabolites of which 158 were quantified. Multivariate analysis uncovered metabolite profile clusters for patients with NAFL, early NASH, and advanced NASH. Also, multiple individual metabolites were associated with histological severity, most notably spermidine which was more than 2-fold lower in advanced fibrosis vs. early fibrosis, in advanced NASH vs. NAFL and in advanced NASH vs. early NASH, suggesting that spermidine exercises a protective effect against development of fibrosing NASH. Furthermore, the results also showed metabolic pathway perturbations between early-NASH and advanced-NASH. In conclusion, using a combination of two reliable analytical platforms (LC-MS and NMR spectroscopy) we identified individual metabolites, metabolite clusters and metabolic pathways that were significantly different between NAFL, early-NASH, and advanced-NASH. These differences provide mechanistic insights as well as potentially important metabolic biomarker candidates that may noninvasively distinguish patients with NAFL, early-NASH, and advanced-NASH. The associations of spermidine levels with less advanced histology merit further assessment of the potential protective effects of spermidine in NAFLD.

// Fariba Tayyari 1 , G.A. Nagana Gowda 2 , Olufunmilayo F. Olopade 3 , Richard Berg 4 , Howard H. Yang 5 , Maxwell P. Lee 5 , Wilfred F. Ngwa 6 , Suresh K. Mittal 7 , Daniel Raftery 2, 8 and Sulma I. Mohammed 7 1 Complex Carbohydrate Research Center, University of Georgia, Athens, Georgia 30602, USA 2 Northwest Metabolomics Research Center, Department of Anesthesiology and Pain Medicine, University of Washington School of Medicine, Seattle, WA 98109, USA 3 The University of Chicago Medical Center, Chicago, IL 60637, USA 4 Indiana University Health Arnett Medical, Lafayette, IN 47905, USA 5 Laboratory of Cancer Biology and Genetics, Center for Cancer Research, National Cancer Institute, NIH, Bethesda, MD 20892, USA 6 Brigham and Women’s Hospital, Dana-Farber Cancer Institute, and Harvard Medical School, Boston, MA 02115, USA 7 Depatment of Comparative Pathobiology and Purdue University Center for Cancer Research, Purdue University, West Lafayette, IN 47907, USA 8 Division of Public Health Sciences, Fred Hutchinson Cancer Research Center, Seattle, WA 98109, USA Correspondence to: Sulma I. Mohammed, email: mohammes@purdue.edu Daniel Raftery, email: draftery@uw.edu Keywords: breast cancer; triple-negative; NMR; African American; Caucasian Received: November 01, 2017 Accepted: January 20, 2018 Published: February 07, 2018 ABSTRACT Breast cancer, a heterogeneous disease with variable pathophysiology and biology, is classified into four major subtypes. While hormonal- and antibody-targeted therapies are effective in the patients with luminal and HER-2 subtypes, the patients with triple-negative breast cancer (TNBC) subtype do not benefit from these therapies. The incidence rates of TNBC subtype are higher in African-American women, and the evidence indicates that these women have worse prognosis compared to women of European descent. The reasons for this disparity remain unclear but are often attributed to TNBC biology. In this study, we performed metabolic analysis of breast tissues to identify how TNBC differs from luminal A breast cancer (LABC) subtypes within the African-American and Caucasian breast cancer patients, respectively. We used High-Resolution Magic Angle Spinning (HR-MAS) 1H Nuclear magnetic resonance (NMR) to perform the metabolomic analysis of breast cancer and adjacent normal tissues (total n=82 samples). TNBC and LABC subtypes in African American women exhibited different metabolic profiles. Metabolic profiles of these subtypes were also distinct from those revealed in Caucasian women. TNBC in African-American women expressed higher levels of glutathione, choline, and glutamine as well as profound metabolic alterations characterized by decreased mitochondrial respiration and increased glycolysis concomitant with decreased levels of ATP. TNBC in Caucasian women was associated with increased pyrimidine synthesis. These metabolic alterations could potentially be exploited as novel treatment targets for TNBC.

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.

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.

There is a lack of experimental reference materials and standards for metabolomics measurements, such as urine, plasma, and other human fluid samples. Reasons include difficulties with supply, distribution, and dissemination of information about the materials. Additionally, there is a long lead time because reference materials need their compositions to be fully characterized with uncertainty, a labor-intensive process for material containing thousands of relevant compounds. Furthermore, data analysis can be hampered by different methods using different software by different vendors. In this work, we propose an alternative implementation of reference materials. Instead of characterizing biological materials based on their composition, we propose using untargeted metabolomic data such as nuclear magnetic resonance (NMR) or gas and liquid chromatography-mass spectrometry (GC-MS and LC-MS) profiles. The profiles are then distributed with the material accompanying the certificate, so that researchers can compare their own metabolomic measurements with the reference profiles. To demonstrate this approach, we conducted an interlaboratory study (ILS) in which seven National Institute of Standards and Technology (NIST) urine Standard Reference Material&reg, s (SRM&reg, s) were distributed to participants, who then returned the metabolomic data to us. We then implemented chemometric methods to analyze the data together to estimate the uncertainties in the current measurement techniques. The participants identified similar patterns in the profiles that distinguished the seven samples. Even when the number of spectral features is substantially different between platforms, a collective analysis still shows significant overlap that allows reliable comparison between participants. Our results show that a urine suite such as that used in this ILS could be employed for testing and harmonization among different platforms. A limited quantity of test materials will be made available for researchers who are willing to repeat the protocols presented here and contribute their data.

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

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 (1)H 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.

Six strictly anaerobic Gram-negative bacteria representing three novel species were isolated from the female reproductive tract. The proposed type strains for each species were designated UPII 199-6T, KA00182T and BV3C16-1T. Phylogenetic analyses based on 16S rRNA gene sequencing indicated that the bacterial isolates were members of the genus Megasphaera . UPII 199-6T and KA00182T had 16S rRNA gene sequence identities of 99.9 % with 16S rRNA clone sequences previously amplified from the human vagina designated as Megasphaera type 1 and Megasphaera type 2, members of the human vaginal microbiota associated with bacterial vaginosis, preterm birth and HIV acquisition. UPII 199-6T exhibited sequence identities ranging from 92.9 to 93.6 % with validly named Megasphaera isolates and KA00182T had 16S rRNA gene sequence identities ranging from 92.6–94.2 %. BV3C16-1T was most closely related to Megasphaera cerevisiae with a 16S rRNA gene sequence identity of 95.4 %. Cells were coccoid or diplococcoid, non-motile and did not form spores. Genital tract isolates metabolized organic acids but were asaccharolytic. The isolates also metabolized amino acids. The DNA G+C content for the genome sequences of UPII 199-6T, KA00182T and BV3C16-1T were 46.4, 38.9 and 49.8 mol%, respectively. Digital DNA–DNA hybridization and average nucleotide identity between the genital tract isolates and other validly named Megasphaera species suggest that each isolate type represents a new species. The major fatty acid methyl esters include the following: C12 : 0, C16 : 0, C16 : 0 dimethyl acetal (DMA) and summed feature 5 (C15 : 0 DMA and/or C14 : 0 3-OH) in UPII 199-6T; C16 : 0 and C16 : 1 cis 9 in KA00182T; C12 : 0; C14 : 0 3-OH; and summed feature 5 in BV3C16-1T. The isolates produced butyrate, isobutyrate, and isovalerate but there were specific differences including production of formate and propionate. Together, these data indicate that UPII 199-6T, KA00182T and BV3C16-1T represent novel species within the genus Megasphaera . We propose the following names: Megasphaera lornae sp. nov. for UPII 199-6T representing the type strain of this species (=DSM 111201T=ATCC TSD-205T), Megasphaera hutchinsoni sp. nov. for KA00182T representing the type strain of this species (=DSM 111202T=ATCC TSD-206T) and Megasphaera vaginalis sp. nov. for BV3C16-1T representing the type strain of this species (=DSM 111203T=ATCC TSD-207T).

The complexity of biological mixtures continues to challenge efforts aimed at unknown metabolite identification in the metabolomics field. To address this challenge, we provide a new method to identify related peaks from individual metabolites in complex NMR spectra. Extractive ratio analysis NMR spectroscopy (E-RANSY) builds on our previously described ratio analysis method [ Wei et al. Anal. Chem. 2011 , 83 , 7616 - 7623 ] and exploits the simplified NMR spectra provided by the extraction of metabolites under varied pH conditions. Under such conditions, metabolites from the same biological specimen are extracted differentially, and the resulting NMR spectra exhibit characteristics favorable for unraveling unknown metabolite peaks using ratio analysis. We demonstrate the utility of the E-RANSY method by extracting carboxylic acid containing metabolites from human urine, one of the highly complex biological mixtures encountered in the metabolomics field. E-RANSY performs better than STOCSY and the original RANSY method and offers new avenues to identify unknown metabolites in complex biological mixtures.

Leigh syndrome is a mitochondrial disease characterized by neurological disorders, metabolic abnormality and premature death. There is no cure for Leigh syndrome; therefore, new therapeutic targets are urgently needed. In Ndufs4-KO mice, a mouse model of Leigh syndrome, we found that Complex I deficiency led to declines in NAD+ levels and NAD+ redox imbalance. We tested the hypothesis that elevation of NAD+ levels would benefit Ndufs4-KO mice. Administration of NAD+ precursor, nicotinamide mononucleotide (NMN) extended lifespan of Ndufs4-KO mice and attenuated lactic acidosis. NMN increased lifespan by normalizing NAD+ redox imbalance and lowering HIF1a accumulation in Ndufs4-KO skeletal muscle without affecting the brain. NMN up-regulated alpha-ketoglutarate (KG) levels in Ndufs4-KO muscle, a metabolite essential for HIF1a degradation. To test whether supplementation of KG can treat Ndufs4-KO mice, a cell-permeable KG, dimethyl ketoglutarate (DMKG) was administered. DMKG extended lifespan of Ndufs4-KO mice and delayed onset of neurological phenotype. This study identified therapeutic mechanisms that can be targeted pharmacologically to treat Leigh syndrome.

An article describing the work that targets NAD metabolism to treat mitochondrial disease

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.

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.

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.

Breast cancer is the second most common cancer among women in the US. The active form of vitamin D, 1,25-dihydroxyvitamin D (1,25(OH)2D), is proposed to inhibit cellular processes and to prevent breast cancer. The current studies investigated the effect of 1,25(OH)2D on glutamine metabolism during cancer progression employing Harvey-ras oncogene transformed MCF10A human breast epithelial cells (MCF10A-ras). Treatment with 1,25(OH)2D significantly reduced intracellular glutamine and glutamate levels measured by nuclear magnetic resonance (NMR) by 23 ± 2% each. Further, 1,25(OH)2D treatment reduced glutamine and glutamate flux, determined by [U-13C5] glutamine tracer kinetics, into the TCA cycle by 31 ± 0.2% and 17 ± 0.4%, respectively. The relative levels of mRNA and protein abundance of the major glutamine transporter, solute linked carrier family 1 member A5 (SLC1A5), was significantly decreased by 1,25(OH)2D treatment in both MCF10A-ras cells and MCF10A which overexpress ErbB2 (HER-2/neu). Consistent with these results, glutamine uptake was reduced by 1,25(OH)2D treatment and the impact was eliminated with the SLC1A5 inhibitor L-γ-Glutamyl-p-nitroanilide (GPNA). A consensus sequence to the vitamin D responsive element (VDRE) was identified in silico in the SLC1A5 gene promoter, and site-directed mutagenesis analyses with reporter gene studies demonstrate a functional negative VDRE in the promoter of the SLC1A5 gene. siRNA-SLC1A5 transfection in MCF10A-ras cells significantly reduced SLC1A5 mRNA expression as well as decreased viable cell number similar to 1,25(OH)2D treatment. SLC1A5 knockdown also induced an increase in apoptotic cells in MCF10A-ras cells. These results suggest 1,25(OH)2D alters glutamine metabolism in MCF10A-ras cells by inhibiting glutamine uptake and utilization, in part through down-regulation of SLC1A5 transcript abundance. Thus, 1,25(OH)2D down-regulation of the glutamine transporter, SLC1A5, may facilitate vitamin D prevention of breast cancer.

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.

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.

Recently, the enhanced resolution and sensitivity offered by chemoselective isotope tags have enabled new and enhanced methods for detecting hundreds of quantifiable metabolites in biofluids using nuclear magnetic resonance (NMR) spectroscopy or mass spectrometry. However, the inability to effectively detect the same metabolites using both complementary analytical techniques has hindered the correlation of data derived from the two powerful platforms and thereby the maximization of their combined strengths for applications such as biomarker discovery of the identification of unknown metabolites. With the goal of alleviating this bottleneck, we describe a smart isotope tag, 15N-cholamine, which possesses two important properties: an NMR sensitive isotope, and a permanent charge for MS sensitivity. Using this tag, we demonstrate the detection of carboxyl group containing metabolites in both human serum and urine. By combining the individual strengths of the 15N label and permanent charge, the smart isotope tag facilitates effective detection of the carboxyl-containing metabolome by both analytical methods. This study demonstrates a unique approach to exploit the combined strength of MS and NMR in the field of metabolomics.

Leigh syndrome (LS) is a congenital mitochondrial disease. Patients with LS develop metabolic abnormality and progressive dysfunctions in brain, skeletal and cardiac muscles, eventually leading to early death. A mouse model of LS with deficiency of a Complex I subunit, Ndufs4-null mice (KO), was used in this study. Depleted NAD + level and NAD + redox imbalance were observed in KO brain and lead to inhibitions of poly (ADP-ribose) polymerase (PARP)-dependent DNA repair and SOD2 activity via protein hyperacetylation. These inhibitions promoted oxidative stress and increased H2Ax phosphorylation, a DNA damage marker, leading to neurological impairments in KO. To counteract the NAD + depletion associated with the pathogenesis of KO, we targeted NAD + salvage pathway to increase NAD + pool size. Supplementation of nicotinamide mononucleotide (NMN), a NAD + precursor, doubled lifespan of KO mice from 55 to 110 days, but did not attenuate neurological impairments, owing to the failure to elevate NAD + levels in brain. We next determined the underlying mechanisms by which NMN extended lifespan of KO without impacting brain NAD + pool. NMN elevated NAD + levels in skeletal and cardiac muscles of KO, resulting in blunted hyperacetylation and attenuated systolic dysfunction. NMN lowered lactate levels in serum and muscles of KO, associated with suppression of hypoxic signaling (lowered HIF1α, LDHA levels). The data suggest a NAD + -sensitive mechanism that suppresses glycolysis in KO treated by NMN via hypoxic signaling. While acetylation levels of HIF1α protein were unchanged in KO, acetylation of glutamate dehydrogenase (GDH) was upregulated in KO and suppressed by NMN. Deacetylation of GDH after NMN treatment promoted upregulation of α-ketoglutarate (KG) level in KO, a co-substrate needed for HIF1α degradation. The results suggested that KG may be beneficial to KO. To determine the therapeutic potential of KG, dimethyl-ketoglutarate (DMKG), a cell permeable form of KG, was administered to KO. DMKG extended lifespan and improved systolic function in KO, associated with suppressed hypoxic signaling. Collectively, this study identified NAD + -dependent pathogenic mechanisms that may lead to translatable interventions for LS and mitochondrial cardiomyopathy.

SummaryInitiation of immune responses requires innate immune sensing, but immune detection of the helminths, protists, and allergens that stimulate type 2 immunity remains poorly understood. In the small intestine, type 2 immune responses are regulated by a tuft cell-ILC2 signaling circuit. Tuft cells express components of a canonical taste transduction pathway, including the membrane channel TRPM5, but the ligands and receptors that activate tuft cells in the small intestine are unknown. Here we identify succinate as the first ligand that activates intestinal tuft cells to initiate type 2 immune responses. Using mRNA-Seq on tuft cells from different tissues, we show that all tuft cells express the intracellular taste transduction pathway, but expression of upstream receptors is tissue-specific. In the small intestine, tuft cells express the succinate receptor SUCNR1. Remarkably, providing succinate in drinking water is sufficient to induce a multifaceted type 2 immune response in the murine small intestine, involving all known components of the tuft-ILC2 circuit. The helminthNippostrongylus brasiliensissecretes succinate as a metabolite, and sensing of both succinate andN. brasiliensisrequires tuft cells and TRPM5, suggesting a novel paradigm in which type 2 immunity monitors microbial metabolism. Manipulation of succinate sensing may have therapeutic benefit in numerous intestinal diseases.

Oral cavity squamous cell carcinoma (OCC) and oropharyngeal squamous cell carcinoma (OPC) are among the most common cancers worldwide and are associated with high mortality and morbidity. The purpose of this study is to identify potential biomarkers to distinguish OCC/OPC from normal controls and to distinguish OCC patients with and without nodal metastasis. We tested saliva samples from 101 OCC, 58 OPC, and 35 normal controls using four analytical platforms (NMR, targeted aqueous by LC-MS/MS, global aqueous and global lipidomics by LC-Q-TOF). Samples from OCC and normal controls were divided into discovery and validation sets. Using linear regression adjusting for age, sex, race and experimental batches, we found the levels of two metabolites (glycine and proline) to be significantly different between OCC and controls (FDR < 0.1 for both discovery and validation sets) but did not find any appreciable differences in metabolite levels between OPC and controls or between OCC with and without nodal metastasis. Four metabolites, including glycine, proline, citrulline, and ornithine were associated with early stage OCC in both discovery and validation sets. Further study is warranted to confirm these results in the development of salivary metabolites as diagnostic markers.